CoSCo Publications

_{The publications of the Adaptive Computing group can be found at http:///www.hiit.fi/adaptive-computing.}

1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2017

2018

E. Jääsaari, J. Leppä-aho, T. Silander and T. Roos. Minimax optimal Bayes mixtures for memoryless sources over large alphabets, to appear in Proc. Int. Conf. on Algorithmic Learning Theory (ALT 2018)
T. Silander, J. Leppä-aho, E. Jääsaari, and T. Roos. Quotient normalized maximum likelihood criterion for learning Bayesian network structures, to appear in Proc. 21st Int. Conf. on Artificial Intelligence and Statistics (AISTATS 2018)

2017

Y. Zou, J. Pensar, and T. Roos (2017). Representing local structure in Bayesian networks by Boolean functions, accepted to Pattern Recognition Letters.
J. Leppä-aho, J. Pensar, T. Roos, and J. Corander (2017). Learning Gaussian graphical models with fractional marginal pseudo-likelihood, to appear in International Journal of Approximate Reasoning, arXiv:1602.07863
Y. Zou and T. Roos (2017). On model selection, Bayesian networks, and the Fisher information integral, New Generation Computing, 35(1) (Special Issue on AMBN 2015), January 2017.

2016

V. Hyvönen, T. Pitkänen, S. Tasoulis, E. Jääsaari, R. Tuomainen, L. Wang, J. Corander, and T. Roos. Fast nearest neighbor search through sparse random projections and voting, in 2016 IEEE International Conference on Big Data (IEEE Big-Data 2016), Washington DC, Dec. 5–8.
T. Roos (2016). Minimum Descption Length Principle, in Sammut, C. and Webb G.I. (eds), Encyclopedia of Machine Learning and Data Mining
T. Heikkilä and T. Roos, (2016). Thematic Section on Studia Stemmatologica, Digital Scholarship in the Humanities 31(3):520–522, doi:10.1093/llc/fqw038
J. Määttä and T. Roos (2016). Maximum parsimony and the skewness test: A simulation study of the limits of applicability, PLOS ONE 11(4):e0152656
L. Wang, S. Tasoulis, T. Roos, and J. Kangasharju (2016). Kvasir: Scalable provision of semantically relevant web content on big data framework, IEEE Transactions on Big Data 2(3):219–233
Y. Zhao, S. Tasoulis, and T. Roos (2016). Manifold visualization via short walks, to appear in EuroVis-2016.
Y. Zou and T. Roos (2016). Sparse Logistic Regression with Logical Features, in Proc. 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2016).
J. Määttä and T. Roos (2016). Robust Sequential Prediction in Linear Regression with Student’s t-distribution, in Proc. 14th International Symposium on Artificial Intelligence and Mathematics (ISAIM 2016).
J. Määttä, D. F. Schmidt, and T. Roos, (2016). Subset Selection in Linear Regression using Sequentially Normalized Least Squares: Asymptotic Theory, Scandinavian Journal of Statistics 43(2):382–395
Tehrani, Q. Nguyen, and T. Roos, (2015). Oral fairy tale or literary fake? Investigating the origins of Little Red Riding Hood using phylogenetic network analysis, Digital Scholarship in the Humanities 31(3):611–636

2015

Marijn Heule, Matti Järvisalo, Florian Lonsing, Martina Seidl, and Armin Biere. Clause Elimination for SAT and QSAT. Journal of Artificial Intelligence Research 53:127-168, 2015.
Adrian Balint, Anton Belov, Matti Järvisalo, and Carsten Sinz. Overview and Analysis of the SAT Challenge 2012 Solver Competition. Artificial Intelligence 223:120-155, 2015.
Sarah Alice Gaggl, Norbert Manthey, Alessandro Ronca, Johannes Peter Wallner, and Stefan Woltran. Improved Answer-Set Programming Encodings for Abstract Argumentation. Theory and Practice of Logic Programming 15(4-5):434-448, 2015.
Lauri Hella, Matti Järvisalo, Antti Kuusisto, Juhana Laurinharju, Tuomo Lempiäinen, Kerkko Luosto, Jukka Suomela, and Jonni Virtema. Weak Models of Distributed Computing, with Connections to Modal Logic. Distributed Computing 28(1):31-53, 2015.
Jeremias Berg, Paul Saikko, and Matti Järvisalo. Improving the Effectiveness of SAT-Based Preprocessing for MaxSAT. In Qiang Yang and Michael Wooldridge, editors, Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), pages 239-245. AAAI Press, 2015.
Wolfgang Dvořák, Matti Järvisalo, Johannes Peter Wallner, and Stefan Woltran. Complexity-Sensitive Decision Procedures for Abstract Argumentation (Extended Abstract). In Qiang Yang and Michael Wooldridge, editors, Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), pages 4073-4077. AAAI Press, 2015.
Antti Hyttinen, Frederick Eberhardt, and Matti Järvisalo. Do-calculus when the True Graph is Unknown. In Tom Heskes and Marina Meila, editors, Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), pages 395-404. AUAI Press, 2015.
Dag Sonntag, Matti Järvisalo, Jose M. Peña, and Antti Hyttinen. Learning Optimal Chain Graphs with Answer Set Programming. In Tom Heskes and Marina Meila, editors, Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), pages 822-831. AUAI Press, 2015.
Brandon Malone, Matti Järvisalo, and Petri Myllymäki. Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical Evaluation. In Tom Heskes and Marina Meila, editors, Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), pages 362-371. AUAI Press, 2015.
Jeremias Berg, Paul Saikko, and Matti Järvisalo. Re-using Auxiliary Variables for MaxSAT Preprocessing. In Proceedings of the IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI 2015), pages 813-820. IEEE Computer Society, 2015.
Paul Saikko, Brandon Malone, and Matti Järvisalo. MaxSAT-Based Cutting Planes for Learning Graphical Models. In Laurent Michel, editor, Proceedings of the 12th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR 2015), volume 9075 of Lecture Notes in Computer Science, pages 345-354. Springer, 2015.
Rémi Brochenin, Thomas Linsbichler, Marco Maratea, Johannes P. Wallner, and Stefan Woltran. Abstract Solvers for Dung's Argumentation Frameworks. In Elizabeth Black, Sanjay Modgil, and Nir Oren, editors, Proceedings of the 3rd Workshop on Theory and Applications of Formal Argumentation (TAFA 2015), revised selected papers, volume 9524 of Lecture Notes in Computer Science, pages 40-58. Springer, 2015.
Jeremias Berg, Antti Hyttinen, and Matti Järvisalo. Applications of MaxSAT in Data Analysis. In ???, editors, Proceedings of the 6th Pragmatics of SAT Workshop (PoS 2015), volume ?? of Easychair Proceedings in Computing, pages ??-??. Easychair, 2015.
Wolfgang Dvořák, Matti Järvisalo, Johannes Peter Wallner, and Stefan Woltran. CEGARTIX v0.4: A SAT-Based Counter-Example Guided Argumentation Reasoning Tool. In Matthias Thimm and Serana Villata, editors, System Descriptions of the First International Competition on Computational Models of Argumentation (ICCMA 2015), 2015. [pdf]
R. Eggeling, T. Roos, P. Myllymäki, I. Grosse (2015). Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data, BMC Bioinformatics 16:375.
Y. Zou and T. Roos (2015). On model selection, Bayesian networks, and the Fisher information integral, to appear in Proc. 2nd Workshop on Advanced Methodologies for Bayesian Networks (AMBN-2015).
Q. Nguyen and T. Roos. Likelihood-based inference of phylogenetic networks from sequence data by PhyloDAG, in Proc. 2nd International Conference on Algorithms for Computational Biology (AlCoB-2015), LNBI 9199, Springer, pp. 126–140.
K. Watanabe and T. Roos. Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies, JMLR (to appear)
T. Ruotsalo, G. Jacucci, P. Myllymäki and S. Kaski, Interactive intent modeling: information discovery beyond search. Communications of the ACM 58 (2015), 1 (January), 86-92.
Liang Wang, Sotiris Tasoulis, Teemu Roos and Jussi Kangasharju. Kvasir: Seamless Intergration of Latent Semantic Analysis-Based Content Provision into Web Browsing. In Proceedings of the 24th International Conference in World Wide Web (WWW 2015) Pages 251-254.

2014

Sotiris Tasoulis, Lu Cheng, Niko Välimäki, Nicholas Croucher, Simon Harris, William Hanage, Teemu Roos, and Jukka Corander, “Random Projection Based Clustering for Population Genomics”, IEEE Big Data 2014: IEEE International Conference on Big Data 2014.
Wolfgang Dvořák, Matti Järvisalo, Johannes Peter Wallner, and Stefan Woltran. Complexity-Sensitive Decision Procedures for Abstract Argumentation. Artificial Intelligence 206:53-78, 2014.
Jeremias Berg and Matti Järvisalo. SAT-Based Approaches to Treewidth Computation: An Evaluation. In Proceedings of the 2014 IEEE 26th International Conference on Tools with Artificial Intelligence (ICTAI 2014), pages 328-335. IEEE Computer Society, 2014.
Emilia Oikarinen and Matti Järvisalo. Answer Set Solver Backdoors. In Eduardo Ferme and Joao Leite, editors, Proceedings of the 14th International Conference on Logics in Artificial Intelligence (JELIA 2014), volume 8761 of Lecture Notes in Computer Science, pages 674-683. Springer, 2014.
Athukorala, K., Oulasvirta, A., Glowacka, D., Vreeken, J. and G. Jacucci, “Interaction Model to Predict Subjective-Specificity of Search Results”, UMAP 2014: 22nd Conference on User Modeling, Adaptation and Personalization.
Glowacka, D. and S. Hore, “Balancing Exploration – Exploitation in Image Retrieval”, UMAP 2014: 22nd Conference on User Modeling, Adaptation and Personalization.
Ruotsalo, T., Peltonen, J., Eugster, M.J.A., Glowacka, D., Reijonen, A., Jacucci, G., Myllymaki, P. and S. Kaski, “IntentRadar: Search User Interface that Anticipates Users Search Intents”, CHI Conference on Human Factors in Computing Systems (extended abstracts).
Melih Kandemir, Akos Vetek, Mehmet Gönen, Arto Klami and Samuel Kaski. Multi-task and multi-view learning of user state. Neurocomputing 139(2):97-106, 2014.
Antti Hyttinen, Frederick Eberhardt, and Matti Järvisalo. Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming. In Jin Tian and Nevin L. Zhang, editors, Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), pages 340-349. AUAI Press, 2014.
Xiannian Fan, Brandon Malone, and Changhe Yuan. Finding Optimal Bayesian Network Structures with Constraints Learned from Data. In Jin Tian and Nevin L. Zhang, editors, Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), pages 200-209. AUAI Press, 2014.
Xiannian Fan, Changhe Yuan, and Brandon Malone. Tightening Bounds for Bayesian Network Structure Learning. In Carla E. Brodley and Peter Stone, editors, Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), pages 2439-2445. AAAI Press, 2014.
Jeremias Berg, Matti Järvisalo, and Brandon Malone. Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability. In Jukka Corander and Samuel Kaski, editors, Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014), pages 86-95, 2014.
R. Eggeling, T. Roos, P. Myllymäki, and I. Grosse. Robust learning of inhomogeneous PMMs. In Proc. 17th International Conference on Artificial Intelligence and Statistics (AISTATS-2014), 2014.
A. Barron, T. Roos, and K. Watanabe. Bayesian properties of normalized maximum likelihood and its fast computation, to appear in Proc. IEEE International Symposium on Information Theory (ISIT-2014), IEEE Press, 2014.
M. Sherman, G. Clark, Y. Yang, S. Sugrim, A. Modig, J. Lindqvist, A. Oulasvirta, and T. Roos. User-generated free-form gestures for authentication: security and memorability. In Proc. 12th International Conference on Mobile Systems, Applications, and Services (MobiSys-2014), ACM Press, 2014.
Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen, and Samuel Kaski. Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. In Carla E. Brodley and Peter Stone, editors, Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), pages 1694-1700. AAAI Press, 2014.
Brandon Malone, Juho-Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, and Petri Myllymäki. Predicting the Hardness of Learning Bayesian Networks. In Carla E. Brodley and Peter Stone, editors, Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), pages 2460-2466. AAAI Press, 2014.
Matti Järvisalo and Janne H. Korhonen. Conditional Lower Bounds for Failed Literals and Related Techniques. In Uwe Egly and Carsten Sinz, editors, Proceedings of the 17th International Conference on Theory and Applications of Satisfiability Testing (SAT 2014), volume 8561 of Lecture Notes in Computer Science, pages 75-84. Springer, 2014.
Brandon M. Malone and Changhe Yuan. A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks. In Madalina Croitoru, Sebastian Rudolph, Stefan Woltran, and Christophe Gonzales, editors, Revised Selected Papers of the Third International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR 2013), volume 8323 of Lecture Notes in Computer Science, pages 111-122. Springer, 2014.
Nitin Sukhija, Brandon Malone, Srishti Srivastava, Ioana Banicescu, and Florina Ciorba. Portfolio-based Selection of Robust Dynamic Loop Scheduling Algorithms using Machine Learning. In IEEE International Symposium on Parallel & Distributed Processing Workshops, pages 1638-1647. IEEE, 2014.
Anton Belov, Daniel Diepold, Marijn J.H. Heule, and Matti Järvisalo (editors). Proceedings of SAT Competition 2014: Solver and Benchmark Descriptions. Volume B-2014-2 of Department of Computer Science Series of Publications B, University of Helsinki, 2014. ISBN 978-951-51-0043-6.
Jussi Määttä, Samuli Siltanen, and Teemu Roos, (2014). A Fixed-Point Image Denoising Algorithm with Automatic Window Selection, in Proc. 5th European Workshop on Visual Information Processing (EUVIP 2014).

2013

Matti Järvisalo and Allen Van Gelder (editors). Theory and Applications of Satisfiability Testing - SAT 2013. Volume 7962 of Lecture Notes in Computer Science, Springer 2013. ISBN 978-3-642-39070-8.
Jeremias Berg and Matti Järvisalo. Optimal Correlation Clustering via MaxSAT. In Proceedings of the 2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW 2013), IEEE Press, 2013.
Antti Hyttinen, Patrik Hoyer, Frederick Eberhardt, and Matti Järvisalo. Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. In Ann Nicholson and Padhraic Smyth, editors, Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI 2013), pages 301-310. AUAI Press, 2013.
Anton Belov, Matti Järvisalo, and Joao Marques-Silva. Formula Preprocessing in MUS Extraction. In Nir Piterman and Scott Smolka, editors, Proceedings of the 19th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2013), volume 7795 of Lecture Notes in Computer Science, pages 110-125. Springer, 2013.
Marijn Heule, Matti Järvisalo, and Armin Biere. Revisiting Hyper Binary Resolution. In Carla Gomes and Meinolf Sellmann, editors, Proceedings of the 10th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR 2013), volume 7874 of Lecture Notes in Computer Science, pages 77-93. Springer, 2013.
Jukka M. Toivanen, Matti Järvisalo, and Hannu Toivonen. Harnessing Constraint Programming for Poetry Composition. In Mary Lou Maher, Tony Veale, Rob Saunders, and Oliver Bown, editors, Proceedings of the <4th International Conference on Computational Creativity (ICCC 2013), pages 160-167. The University of Sydney, 2013.
Marijn Heule, Matti Järvisalo, and Armin Biere. Covered Clause Elimination. In Andrei Voronkov, Geoff Sutcliffe, Matthias Baaz, and Christian Fermüller, editors, Short Paper Proceedings of the 17th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR-17 / 2010), volume 13 of EasyChair Proceedings in Computing, pages 41-46, 2013.
Adrian Balint, Anton Belov, Marijn J.H. Heule, and Matti Järvisalo (editors). Proceedings of SAT Competition 2013: Solver and Benchmark Descriptions. Volume B-2013-1 of Department of Computer Science Series of Publications B, University of Helsinki, 2013. ISBN 978-952-10-8991-6.
K. Watanabe, T. Roos, and P. Myllymäki (2013). Achievability of asymptotic minimax regret in online and batch prediction, in Proc. 5th Asian Conference on Machine Learning (ACML-2013).
A. Oulasvirta, T. Roos, A. Modig, and L. Leppänen, (2013). Information capacity of full-body movements, in Proc. 2013 ACM SIGCHI Conference on Human Factors in Computing Systems (CHI-2013), ACM. Best paper honorable mention award.
T. Roos and Y. Zou, (2013). Keep it simple stupid—On the effect of lower-order terms in BIC-like criteria, invited paper in Proc. 2013 Information Theory and Applications Workshop, (ITA-2013).
Dorota Głowacka, Tuukka Ruotsalo, Ksenia Konyushkova, Kumaripaba Athukorala, Samuel Kaski, and Giulio Jacucci. Directing exploratory search: Reinforcement learning from user interactions with keywords. In Proceedings of IUI'13, International Conference on Intelligent User Interfaces, pages 117–128, New York, NY, 2013. ACM. Best paper award.
Dorota Głowacka, Tuukka Ruotsalo, Ksenia Konyushkova, Kumaripaba Athukorala, Samuel Kaski, and Giulio Jacucci. “SciNet: A system for browsing scientific literature through keyword manipulation.” In IUI'13 Companion, International Conference on Intelligent User Interfaces, pages 61–62, New York, NY, 2013. ACM.
Tuukka Ruotsalo, Kumaripaba Athukorala, Dorota Glowacka, Ksenia Konyushkova, Antti Oulasvirta, Samuli Kaipiainen, Samuel Kaski, and Giulio Jacucci. “Supporting exploratory search tasks with interactive user modeling”. In Proceedings of ASIST 2013, the 76th ASIS&T Annual Meeting, accepted for publication.
Tuukka Ruotsalo, Jaakko Peltonen, Manuel J.A. Eugster, Dorota Glowacka, Ksenia Konyushkova, Kumaripaba Athukorala, Ilkka Kosunen, Aki Reijonen, Petri Myllymäki, Giulio Jacucci, and Samuel Kaski. Directing exploratory search with interactive intent modeling. Pp. 1759-1764 in Proceedings of CIKM 2013, ACM Conference on Information and Knowledge Management.
Arto Klami. Bayesian object matching. Machine Learning 92(2):225-250, 2013.
Arto Klami, Guillaume Bouchard, and Abhishek Tripathi. Group-sparse embeddings in collective matrix factorization. arXiv preprint arXiv:1312.5921, 2013.
Sourav Bhattacharya, Santi Phithakkitnukoon, Petteri Nurmi, Arto Klami, Marco Veloso, and Carlos Bento. Gaussian process-based predictive modeling for bus ridership. In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication, pages 1189-1198, ACM, 2013.
Sami Remes, Arto Klami, and Samuel Kaski. Characterizing unknown events in MEG data with group factor analysis. In Proceedings of MLINI 2013: Workshop on machine learning and interpretation in neuroimaging. 2013.
Changhe Yuan and Brandon Malone. Learning Optimal Bayesian Networks: A Shortest Path Perspective. Journal of Artificial Intelligence Research. 48: 23-65. October 2013.
Babi Ramesh Reddy Nallamilli, Jian Zhang, Hana Mujahid, Brandon Malone, Susan Bridges and Zhaohua Peng. Polycomb Group Gene OsFIE2 Regulates Rice (Oryza sativa) Seed Development and Grain Filling via a Mechanism Distinct from Arabidopsis. PLoS Genetics. 9(3). March 2013.
Brandon Malone and Changhe Yuan. Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks. In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence. July 2013.
Srishti Srivastava, Brandon Malone, Nitin Sukhija, Ioana Banicescu Florina Ciorba. Predicting the Flexibility of Dynamic Loop Scheduling Using an Artificial Neural Network. In Proceedings of the 12th International Symposium on Parallel and Distributed Computing. June 2013.

2012

T. Roos, P. Myllymäki, and T. Jaakkola, Editorial: Special issue on the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010). International Journal of Approximate Reasoning 59 (2012) 9, 1303-1304.
H. Wettig, J. Nouri, K. Reshetnikov, and R. Yangarber, Information-theoretic Methods for Analysis and Inference in Etymology. Pp. 53-56 in Proceedings of the Fifth Workshop on Information-theoretic Methods in Science and Engineering.
H. Wettig, K. Reshetnikov, and R. Yangarber, Using Context and Phonetic Features in Models of Etymological Sound Change. Pp. 108-116 in Proceedings of the EACL 2012 Joint Workshop of LINGVIS.
Matti Järvisalo, Armin Biere, and Marijn Heule. Simulating Circuit-Level Simplifications on CNF. Journal of Automated Reasoning 49(4):583-619, 2012.
Matti Järvisalo, Arie Matsliah, Jakob Nordström, and Stanislav Živný. Relating Proof Complexity Measures and Practical Hardness of SAT. In Michela Milano, editor, Proceedings of the 18th International Conference on Principles and Practice of Constraint Programming (CP 2012), volume 7514 of Lecture Notes in Computer Science (LNCS), pages 316-331. Springer, 2012.
Matti Järvisalo, Marijn Heule, and Armin Biere. Inprocessing Rules.
In Bernhard Gramlich, Dale Miller, and Uli Sattler, editors, Proceedings of the 6th International Joint Conference on Automated Reasoning (IJCAR 2012), volume 7364 of Lecture Notes in Computer Science (LNCS/LNAI), pages 355-370. Springer, 2012.
Wolfgang Dvořák, Matti Järvisalo, Johannes Peter Wallner, and Stefan Woltran. Complexity-Sensitive Decision Procedures for Abstract Argumentation. In Thomas Eiter and Sheila McIlraith, editors, Proceedings of the 13th International Conference on Principles of Knowledge Representation and Reasoning (KR 2012), pages 54-64. AAAI Press, 2012.
Matti Järvisalo, Petteri Kaski, Mikko Koivisto, and Janne H. Korhonen. Finding Efficient Circuits for Ensemble Computation. In Alessandro Cimatti and Roberto Sebastiani, editors, Proceedings of the 15th International Conference on Theory and Applications of Satisfiability Testing (SAT 2012), volume 7317 of Lecture Notes in Computer Science, pages 369-382. Springer, 2012.
Lauri Hella, Matti Järvisalo, Antti Kuusisto, Juhana Laurinharju, Tuomo Lempiäinen, Kerkko Luosto, Jukka Suomela, and Jonni Virtema. Weak Models of Distributed Computing, with Connections to Modal Logic. In Darek Kowalski and Alessandro Panconesi, editors, Proceedings of the 31st Annual ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing (PODC 2012), pages 185-194. ACM Press, 2012.
Matti Järvisalo, Daniel Le Berre, Olivier Roussel, and Laurent Simon. The International SAT Solver Competitions. AI Magazine 33(1):89-92, 2012.
Adrian Balint, Anton Belov, Daniel Diepold, Simon Gerber, Matti Järvisalo, and Carsten Sinz (editors). Proceedings of SAT Challenge 2012: Solver and Benchmark Descriptions. Volume B-2012-2 of Department of Computer Science Series of Publications B, University of Helsinki, 2012. ISBN 978-952-10-8106-4.
Wolfgang Dvořák, Matti Järvisalo, Johannes Peter Wallner, and Stefan Woltran. CEGARTIX: A SAT-Based Argumentation System. In 3rd Workshop on Pragmatics of SAT (PoS 2012), 2012.
B. Malone and C. Yuan. A Bounded Error, Anytime Parallel Algorithm for Exact Bayesian Network Structure Learning. In Proceedings of the 6th European Workshop on Probabilistic Graphical Models (PGM-2012), Granada, Spain, September 2012.
A. Oulasvirta, A. Pihlajamaa, J. Perkiö, T. Vähakangas, D. Ray, N. Vainio, P. Myllymäki, T. Hasu, Long-term Effects of Ubiquitous Surveillance at Home. In Proceedings of the 14th International Conference on Ubiquitous Computing (Ubicomp), September, 2012.
S. de Rooij, W. Kotłowski, J. Rissanen, P. Myllymäki, T. Roos, and K. Yamanishi (editors), Proceedings of the Fifth Workshop on Information Theoretic Methods in Science and Engineering (WITMSE 2012).
C. Yuan and B. Malone, An Improved Admissible Heuristic for Finding Optimal Bayesian Networks. In the proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI-2012), Catalina Island, California, August 2012.
C.D. Giurcaneanu, P. Luosto and P. Kontkanen, On The Performance Of Histogram-Based Entropy Estimators. In Proceedings of the 2012 IEEE International Workshop on Machine Learning for Signal Processing (MLSP'2012), September 2012, Santander, Spain.
P. Luosto, C.D. Giurcaneanu and P. Kontkanen, Construction of irregular histograms by penalized maximum likelihood: a comparative study. IEEE Information Theory Workshop 2012 (ITW), Lausanne, Switzerland, 3-7 September 2012.
J. Rissanen, Optimal Estimation of Parameters. Cambridge University Press, 2012.
S. Bhattacharya, P. Floréen, A. Forsblom, S. Hemminki, P. Myllymäki, P. Nurmi, T. Pulkkinen, A. Salovaara, Ma$$iv€ - An Intelligent Mobile Grocery Assistant. In Proceedings of the 8th International Conference on Intelligent Environments (IE'12, June 2012, Guanajuato, Mexico).

2011

T. Roos and Y. Zou, Analysis of Textual Variation by Latent Tree Structures. In Proceedings of the 2011 ICDM IEEE International Conference on Data Mining, Vancouver, December 2011. IEEE Computer Society Press.
P. Luosto and P. Kontkanen, Clustgrams: an extension to histogram densities based on the minimum description length principle. Central European Journal of Computer Science 1 (2011) 4, 466-481.
A. Oulasvirta, J. Perkiö, H. Hietanen and S. Tamminen, Rethinking ethical practices for the Helsinki Privacy Experiment. CHI 2011 Workshop on Ethics, Logs and Videotape: Ethics in Large Scale Trials & User Generated Content. Vancouver, Canada.
Jorma Rissanen, Petri Myllymäki, Teemu Roos, Ioan Tabus and Kenji Yamanishi (eds.), Proceedings of the Fourth Workshop on Information Theoretic Methods in Science and Engineering (Witmse 2011). University of Helsinki, Department of Computer Science, Report C-2011-45.
A. Carvalho, T. Roos, A. Oliveira, and P. Myllymäki. Discriminative learning of Bayesian networks via factorized conditional log-likelihood. Journal of Machine Learning Research 12 (2011), 2181-2210.
T. Pulkkinen, T. Roos, and P. Myllymäki. Semi-supervised learning for WLAN positioning, In Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN-2011), edited by T. Honkela, W. Duch, M. Girolami, M. and S. Kaski. Lecture Notes in Computer Science, Vol. 6792, Springer-Verlag, 2011.
T. Roos. Yksinkertainen on kaunista: Okkamin partaveitsi tilastollisessa mallinnuksessa, Tietojenkäsittelytiede 32, 48–63.

2010

P. Myllymäki, T. Roos and T. Jaakkola (eds.), Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010). HIIT Publications 2010-2.
K. Yamanishi, I. Kontoyiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus (eds.), Proceedings of the Third Workshop on Information Theoretic Methods in Science and Engineering. TICSP series 55, Tampere International Center for Signal Processing, 2010.
J. Perkiö, A. Tuominen, T. Vähäkangas and P. Myllymäki, Image Similarity: From Syntax to Weak Semantics. Multimedia Tools and Applications, DOI: 10.1007/s11042-010-0562-7, July 14, 2010.
T. Silander, T. Roos, and P. Myllymäki, Learning Locally Minimax Optimal Bayesian Networks, International Journal of Approximate Reasoning 51 (2010) 5 (June), 544-557.
P. Maksimainen, Finding groups in virtual communities. M.Sc. thesis, Report C-2010-28, Department of Computer Science, University of Helsinki, Finland.
J. Rissanen, T. Roos, and P. Myllymäki, Model Selection by Sequentially Normalized Least Squares, Journal of Multivariate Analysis 101 (2010) 4 (April), 839-849.
J. Rissanen, The MDL Principle, in C. Sammut and G.I. Webb (editors), Encyclopedia of Machine Learning, Springer, 2010.
T. Roos, Terveisiä huippuyliopistoista, Tietojenkäsittelytiede 30 (2010), 7-12.
D.F. Schmidt and T. Roos. On the consistency of sequentially normalized least squares, invited paper (extended abstract) in Proc. 3rd Workshop on Information Theoretic Methods in Science and Engineering (WITMSE-10), Tampere International Center for Signal Processing.
P.-H. Lai, T. Roos, and J. O'Sullivan, MDL Hierarchical Clustering for Stemmatology, in Proceedings of the 2010 IEEE International Symposium on Information Theory (ISIT-2010).
Y. Zou, (2010). Structural EM methods in phylogenetics and stemmatology, Master's Thesis, Department of Computer Science, University of Helsinki.

2009

J. Perkiö, T. Tuytelars and W. Buntine, Exploring Scale-Induced Feature Hierarchies in Natural Images. Pp. 25-31 in Proceedings of the Eight International Conference on Machine Learning and Applications, edited by M. A. Wani, M. Kantardzic, V. Palade, L. Kurgan and Y. Qi. IEEE Computer Society, 2009.
T. Mononen, Computing the Stochastic Complexity of Simple Probabilistic Graphical Models. Doctoral dissertation, University of Helsinki. Department of Computer Science, Series of Publications A, Report A-2009-10.
P. Kontkanen, Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering. Doctoral dissertation, University of Helsinki. Department of Computer Science, Series of Publications A, Report A-2009-11.
J. Perkiö, A. Tuominen and P. Myllymäki, Image Similarity: From Syntax to Weak Semantics using Multimodal Features with Application to Multimedia Retrieval. Pp. 213-219 in Proceedings of the 2009 International Conference on Multimedia Information Networking and Security. IEEE Computer Society, 2009.
J. Perkiö and P. Myllymäki, Magrathea: Building and Analyzing Ubiquitous and Social Systems. Pp. 66-75 in Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technologies, edited by P. Boldi, G. Vizzari, G. Pasi and R. Baeza-Yates. IEEE Computer Society, 2009.
J. Perkiö and A. Hyvärinen, Modelling Image Complexity by Independent Component Analysis, with Application to Content-Based Image Retrieval (winner of the best student paper award). Pages 704-714 in Proceedings of the 19th International Conference on Artificial Neural Networks (ICANN-09), edited by C. Alippi, M. Polycarpou, C. Panayiotou and G. Ellinas. Lecture Notes in Computer Science 5769, Springer 2009.
T. Roos, P. Myllymäki, and J. Rissanen, MDL Denoising Revisited. IEEE Trans. Signal Processing 57 (2009) 9 (September), 3347-3360.
K. Kumpulainen, P. Myllymäki, R. Smeds, J. Kronqvist and P. Pöyry-Lassila, VISCI Virtual Intelligent Space for Collaborative Innovation - Project Description. Pp. 75-82 in Proceedings of the 1st International Symposium on Tangible Software Enginering Education (STANS09), edited by T. Nakamura, H. Kameda, S. Iwashita, A. Takashima and H. Maruyama.
J. Heikkonen, I. Kontoyiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus (eds.), Proceedings of the Second Workshop on Information Theoretic Methods in Science and Engineering. TICSP series 49, Tampere International Center for Signal Processing, 2009.
T. Merivuori and T. Roos, Some Observations on the Applicability of Normalized Compression Distance to Stemmatology. In Proceedings of the Second Workshop on Information Theoretic Methods in Science and Engineering, edited by J. Heikkonen, I. Kontoyiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus. TICSP series 49, Tampere International Center for Signal Processing, 2009.
P. Myllymäki, A framework for MDL clustering. In Proceedings of the Second Workshop on Information Theoretic Methods in Science and Engineering, edited by J. Heikkonen, I. Kontoyiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus. TICSP series 49, Tampere International Center for Signal Processing, 2009.
E. Elovaara and P. Myllymäki, MDL-based attribute models in naive Bayes classification. In Proceedings of the Second Workshop on Information Theoretic Methods in Science and Engineering, edited by J. Heikkonen, I. Kontoyiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus. TICSP series 49, Tampere International Center for Signal Processing, 2009.
T. Roos and B. Yu, Recovering Sparse Models by Parameter Transformations: Applications in Markov Models and Logistic Regression. In Proceedings of the Second Workshop on Information Theoretic Methods in Science and Engineering, edited by J. Heikkonen, I. Kontoyiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus. TICSP series 49, Tampere International Center for Signal Processing, 2009.
J. Rissanen, Model Selection and Testing by the MDL Principle. Chapter 2 in F. Emmert-Streib and M. Dehmer, eds., Information Theory and Statistical Learning, Springer, 2009.
T. Roos and T. Heikkilä, Evaluating Methods for Computer-Assisted Stemmatology using Artificial Benchmark Data Sets. Literary & Linguistic Computing, 2009, doi:10.1093/llc/fqp002.
T. Silander, The Most Probable Bayesian Network and Beyond. Doctoral dissertation, University of Helsinki. Department of Computer Science, Series of Publications A, Report A-2009-2.
T. Silander, T. Roos, and P. Myllymäki, Locally Minimax Optimal Predictive Modeling with Bayesian Networks. Pp. 504-511 in Proceedings of the 12th International Conference on Artificial Intelligence and Statistics, edited by D. van Dyk and M. Welling. JMLR Workshop and Conference Proceedings, Volume 5: AISTATS 2009.
T. Roos and B. Yu, Sparse Markov Source Estimation via Transformed Lasso, IEEE Information Theory Workshop (ITW-09), Volos, Greece, June 10–12, 2009.
T. Roos and B. Yu, Estimating Sparse Models from Multivariate Discrete Data via Transformed Lasso, Information Theory and Applications Workshop (ITA-09), San Diego CA, USA, February 8–13, 2009.

2008

T. Mononen and P. Myllymäki, On Recurrence Formulas for Computing the Stochastic Complexity. Pp. 281-286 in Proceedings of the 2008 International Symposium on Information Theory and its Applications (ISITA2008), December 7-10, 2008, Auckland, New Zealand.
A. Pernestål, H. Wettig, T. Silander, M. Nyberg and P. Myllymäki, A Bayesian Approach to Learning in Fault Isolation. Pp. 143-150 in Proceedings of The 19th International Workshop on Principles of Diagnosis (DX-08), edited by A. Grastien, W. Mayer, and M. Stumptner. September 22-24, 2008, Blue Mountains, NSW, Australia.
T. Silander, T. Roos, P. Kontkanen, and P. Myllymäki, Factorized NML Criterion for Learning Bayesian Network Structures. Pp. 257-264in Proceedings of the 4th European Workshop on Probabilistic Graphical Models (PGM-08), edited by M. Jaeger and T. Nielsen. September 17–19, Hirtshals, Denmark.
T. Mononen and P. Myllymäki, Computing the Multinomial Stochastic Complexity in Sub-Linear Time. Pp. 209-216 in Proceedings of the 4th European Workshop on Probabilistic Graphical Models (PGM-08), edited by M. Jaeger and T. Nielsen. September 17–19, Hirtshals, Denmark.
J. Heikkonen, I. Kontoiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus (eds), Proceedings of the First Workshop on Information Theoretic Methods in Science and Engineering. TICSP Series #43, Tampere International Center for Signal Processing, 2008.
P. Myllymäki, Recent Advances in Computing the NML for Discrete Bayesian Networks. In Proceedings of the First Workshop on Information Theoretic Methods in Science and Engineering, edited by J. Heikkonen, I. Kontoiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus. TICSP Series #43, Tampere International Center for Signal Processing, 2008.
J. Rissanen, Minimum Description Length, Scholarpedia, 3(8):6727, 2008.
T. Roos and J. Rissanen, On Sequentially Normalized Maximum Likelihood Models. In Proceedings of the First Workshop on Information Theoretic Methods in Science and Engineering, edited by J. Heikkonen, I. Kontoiannis, E. Liski, P. Myllymäki, J. Rissanen and I. Tabus. TICSP Series #43, Tampere International Center for Signal Processing, 2008.
P. Kontkanen and P. Myllymäki, An Empirical Comparison of NML Clustering Algorithms. In Proceedings of the 2008 International Conference on Information Theory and Statistical Learning (ITSL-08).
T. Mononen and P. Myllymäki, On the Multinomial Stochastic Complexity and its Connection to the Birthday Problem. In Proceedings of the 2008 International Conference on Information Theory and Statistical Learning (ITSL-08).
J. Perkiö, P. Myllymäki, V. Tuulos and P. Boda, Magrathea: A Mobile Agent- and Sensing Platform. In Proceedings of the 2008 International Conference on Wireless Networks (ICWN-08).
D. McAllester and P. Myllymäki (eds.), Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI-08), July 2008, Helsinki, Finland.
T. Roos, Monte Carlo Estimation of Minimax Regret with an Application to MDL Model Selection. Pp. 284-288 in Proceedings of the 2008 IEEE Information Theory Workshop. IEEE 2008.
T. Mononen and P. Myllymäki, Computing the NML for Bayesian Forests via Matrices and Generating Polynomials. Pp. 276-280 in Proceedings of the 2008 IEEE Information Theory Workshop. IEEE 2008.
T. Roos, T. Silander, P. Kontkanen, and P. Myllymäki, Bayesian Network Structure Learning using Factorized NML Universal Models. Pp. 272-276 in Proceedings of the 2008 Information Theory and Applications Workshop, San Diego, CA, January-February 2008.
P. Myllymäki, T. Roos, T. Silander, P. Kontkanen and H. Tirri, Factorized NML Models. Chapter 11 in Festschrift in Honour of Jorma Rissanen , edited by P. Grünwald, P. Myllymäki, I. Tabus, M. Weinberger and B. Yu.
P. Grünwald, P. Myllymäki, I. Tabus, M. Weinberger and B. Yu (eds.), Festschrift in Honor of Jorma Rissanen. TICSP Series #38, Tampere International Center for Signal Processing, 2008. Presented at the 2008 IEEE Information Theory Workshop.

2007

P. Kontkanen, H. Wettig and P. Myllymäki, NML Computation Algorithms for Tree-Structured Multinomial Bayesian Networks. EURASIP Journal on Bioinformatics and Systems Biology, Vol. 2007, Article ID 90947, 11 pages.
J. Rissanen, P. Grünwald, J. Heikkonen, P. Myllymäki, T. Roos, J. Rousu, Information Theoretic Methods for Bioinformatics, guest editorial for a special issue of EURASIP Journal on Bioinformatics and Systems Biology, Vol. 2007.
J. Rissanen, Information and Complexity in Statistical Modeling. Springer, 2007.
Jürgen Scheible and Ville Tuulos, Mobile Python: Rapid Prototyping of Applications on the Mobile Platform. Wiley, 2007.
T. Mononen and P. Myllymäki, Fast NML Computation for Naive Bayes Models. Pp. 151-160 in the Proceedings of the 10th International Conference on Discovery Science, edited by V. Corruble, M. Takeda and E. Suzuki. Lecture Notes in Artificial Intelligence 4755, Springer 2007.
H. Wettig, P. Kontkanen and P. Myllymäki, Calculating the Normalized Maximum Likelihood Distribution for Bayesian Forests. IADIS International Journal on Computer Science and Information Systems 2 (2007) 2 (October). Also: In Proceedings of the IADIS International Conference on Intelligent Systems and Agents 2007. Lisbon, Portugal, 2007 (Outstanding paper award).
V. Tuulos, Design and Implementation of a Content-Based Search Engine. M.Sc. Thesis, Department of Computer Science, University of Helsinki.
T. Silander and P. Kontkanen and P. Myllymäki, On Sensitivity of the MAP Bayesian Network Structure to the Equivalent Sample Size Parameter. Pp. 360-367 in the Proceedings of the The 23rd Conference on Uncertainty in Artificial Intelligence (UAI-2007), edited by R. Parr and L. van der Gaag. AUAI Press, 2007.
P. Kontkanen and P. Myllymäki, A linear-time algorithm for computing the multinomial stochastic complexity. Information Processing Letters 103 (2007) 6 (September), 227-233.
T. Laine, Decision and Learning Model Selection for Complex Adaptive Systems (extended abstract). P. 1798 in Proceedings of the 29th Annual Conference of the Cognitive Science Society, edited by D. S. McNamara and J. G. Trafton. Cognitive Science Society, 2007.
T. Laine, Learning and Decision Model Selection for a Class of Complex Adaptive Systems. Pp. 273-278 in Proceedings of the 8th International Conference on Cognitive Modeling, edited by R.L. Lewis, T.A. Polk, and J.E. Laird. Taylor & Francis/Psychology Press, 2007.
M. Miettinen and A. Oulasvirta, Predicting time-sharing in mobile interaction. User Modeling and User-Adapted Interaction (UMUAI) 17 (2007) 5 (December), 475-510.
V. Tuulos, J. Scheible and H. Nyholm, Combining Web, Mobile Phones and Public Displays in Large-Scale: Manhattan Story Mashup. Pp. 37-54 in Proceedings of the Fifth International Conference on Pervasive Computing, edited by A. LaMarca M. Langheinrich and K.N. Truong. Lecture Notes in Computer Science 4480, Springer 2007.
P. Kontkanen and P. Myllymäki, MDL Histogram Density Estimation. In Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS 2007), Puerto Rico, March 2007.
J. Rissanen, T. Roos, Conditional NML Universal Models. Invited talk at the Information Theory and Applications Workshop, San Diego, CA, January–February, 2007.
T. Roos, Statistical and Information-Theoretic Methods for Data Analysis, Doctoral Dissertation, Department of Computer Science, University of Helsinki.
P. Nokelainen, T. Silander, P. Ruohotie and H. Tirri, Investigating the Number of Non-linear and Multi-modal Relationships Between Observed Variables Measuring Growth-oriented Atmosphere. Quality and Quantity 41 (2007) 6 (December), 869-890.

2006

K. Deforche, T. Silander, R. Camacho, Z . Grossman, M. A. Soares, K. Van Laethem, R. Kantor, Y. Moreau and A.-M. Vandamme, Analysis of HIV-1 pol sequences using Bayesian Networks: implications for drug resistance. Bioinformatics, 22 (2006), 24 (December), 2975-2979.
S. Bloehorn, W. Buntine, A. Hotho, Editors' Introduction to the Special Issue "Learning in Web Search". Informatica, An International Journal of Computing and Informatics, 30 (2006) 2.
J. Fokker, J. Pouwelse, and W. Buntine, Tag-Based Navigation for Peer-to-Peer Wikipedia. Collaborative Web Tagging Workshop, 15th International World Wide Web Conference (WWW2006).
O.-P. Ryynänen, M. Puhakka, P. Myllymäki, P. Palomäki, V. Anttonen, R. Jukola and J. Takala, Sairaalaan lähettämisen arvointi Bayesin verkkomallilla. Finnish Medical Journal, Vol. 61 (2006), No. 51-52, 5353-5358.
J. Perkiö, V. Tuulos, M. Hermersdorf, H. Nyholm, J. Salminen and H. Tirri, Utilizing Rich Bluetooth Environments for Identity Prediction and Exploring Social Networks as Techniques for Ubiquitous Computing. Pp. 137-141 in Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, edited by T. Nishida, Z. Shi, U. Visser, X. Wu, J. Liu, B. Wah, W. Cheung and Y.-M. Cheung. IEEE Computer Society, 2006.
M. Hermersdorf, H. Nyholm, J. Salminen, H. Tirri, J. Perkiö and V. Tuulos, Sensing in Rich Bluetooth Environments, Pp. 27-31 in Working Notes of the Workshop on World-Sensor-Web (WSW'2006), edited by P. Boda.
E. Soini, J. Martikainen, J. Lahtinen, P. Myllymäki, P. Kontkanen, K. Valtonen and O.-P. Ryynänen, Efficient Data Mining And Probabilistic Inference With P-Course: A Bayesian Method With Multilevel Priors For Medical Applications. The ISPOR 9th Annual European Congress Presentations in Value in Health: The Journal of the International Society for Pharmaeconomics and Outcomes Research, Vol.9 (2006), No. 6 (November/December), A270. .
M. Beigbeder, W. Buntine and W.-G. Yee (eds.), Proceedings of the Second Workshop on Open Source Information Retrieval (OSIR06).
J. Fokker, W. Buntine and J. Pouwelse, Tagging in Peer-to-Peer Wikipedia - A Method to Induce Cooperation. Pp. 39-45 in Proceedings of the Second Workshop on Open Source Information Retrieval (OSIR06), edited by M. Beigbeder, W. Buntine and W.-G. Yee.
W. Buntine, M. Taylor and F. Lagunas, Standards for Open Source Information Retrieval. Pp. 68-72 in Proceedings of the Second Workshop on Open Source Information Retrieval (OSIR06), edited by M. Beigbeder, W. Buntine and W.-G. Yee.
W.-G. Yee, M. Beigbeder and W. Buntine, SIGIR06 Workshop Report: Open Source Information Retrieval Systems. ACM SIGIR Forum 40 (2006) 2 (December), 61-65.
L. Zhou and W. Buntine, Web Search Technology - from Search to Semantic Search. In ASWC 2006 Workshops Proceedings, edited by G. Li, Y. LIang and M. Ronchetti. Jilin University Press, 2006.
P. Kontkanen and P. Myllymäki, Information-Theoretically Optimal Histogram Density Estimation. Technical Report HIIT-2006-2. Helsinki Institute for Information Technology, 2006.
T. Silander and P. Myllymäki, A Simple Approach for Finding the Globally Optimal Bayesian Network Structure. Pp. 445-452 in Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence (UAI-2006), edited by R. Dechter and T. Richardson. AUAI Press, 2006.
W. Buntine and A. Jakulin, Discrete Components Analysis. Pp. 1-33 in Subspace, Latent Structure and Feature Selection Techniques, edited by C. Saunders, M. Grobelnik, S. Gunn and J. Shawe-Taylor. Springer-Verlag 2006.
T. Roos, T. Heikkilä and P. Myllymäki, A Compression-Based Method for Stemmatic Analysis. Pp. 805-806 in Proceedings of the 17th European Conference on Artificial Intelligence (ECAI 2006), edited by G. Brewka, S. Coradeschi, A. Perini and P. Traverso. IOS Press, 2006.
J. Lahtinen, P. Myllymäki and O.-P. Ryynänen, P-Course: Medical Applications of Bayesian Classification with Informative Priors. In Proceedings of the ECAI'2006 Workshop on AI Techniques in Healthcare: Evidence-Based Guidelines and Protocols, edited by A. ten Teije, S. Miksch and P. Lucas.
W. Buntine and K. Valtonen, Topic Models in ALVIS. In Book of Abstracts of the International Workshop on Intelligent Information Access (IIIA-2006), Helsinki, FInland, July 2006.
V. Tuulos and A. Tuominen, Some Key Challenges in Web Crawlers and Content-Based Search Engines. In Book of Abstracts of the International Workshop on Intelligent Information Access (IIIA-2006), Helsinki, FInland, July 2006.
A. Tuominen and V. Tuulos, BulkFS: a Distributed Fault-Tolerant File System for Massive Data Application. In Book of Abstracts of the International Workshop on Intelligent Information Access (IIIA-2006), Helsinki, FInland, July 2006.
T. Roos, P. Grünwald, P. Myllymäki and H. Tirri, Generalization to Unseen Cases. Pp. 1129-1136 in Advances in Neural Information Processing Systems 18 (NIPS 05), edited by Y. Weiss, B.Schölkopf and J. Platt. MIT Press, Cambridge, MA, 2006.
M. Miettinen, J. Kurhila, P. Nokelainen and H. Tirri, Supporting Open-Ended Discourse with Transparent Groupware. International Journal of Web Based Communities, Vol. 2, No. 1, pp. 17-30.
M. Jaeger, J. Nielsen and T. Silander, Learning probabilistic decision graphs. International Journal of Approximate Reasoning, 42 (2006), 84-100.

2005

T. Lepola, Inferring relevance from Eye Movements using Generic Neural Microcircuits. Pp. 31-36 in Proceedings of the NIPS 2005 Workshop on Machine Learning for Implicit Feedback and User Modeling, edited by K. Puolamäki and S. Kaski.
W. Buntine, Static Ranking of Web Pages, and Related Ideas. Workshop on Open Source Web Information Retrieval at Web Intelligence WI 2005. September 19th, Compiegne, France
A. Pajala, A. Jakulin and W. Buntine, Eduskuntaryhmien äänestyskäyttäytyminen ja -koheesio vuoden 2003 valtiopäivillä. Politiikka 47 (2005) 3, 205-217.
W. Buntine, K. Aberer, I. Podnar and M. Rajman, Opportunities from Open Source Search. Invited talk at Web Intelligence WI 2005. September 19th, Compiegne, France
S. Bloehdorn, W. Buntine and A. Hotho (editors), Proceedings of Learning in Web Search (LWS 2005), An International Workshop at the 22nd International Conference on Machine Learning (ICML 2005).
W. Buntine, J. Löfström, S. Perttu and K. Valtonen, Topic-Specific Scoring of Documents for Relevant Retrieval. Pp. 34-41 in Workshop on Learning in Web Search (LWS 2005).
P. Kontkanen, P. Myllymäki, Analyzing the Stochastic Complexity via Tree Polynomials. Technical Report HIIT-2005-4.
W. Buntine, Open Source Search: A Data Mining Platform. SIGIR Forum 39 (2005) 1, 4-10.
W. Buntine, K. Valtonen and M. P. Taylor, The ALVIS Document Model for a Semantic Search Engine. Proceedings of the 2nd European Semantic Web Conference (ESWC 2005), Heraklion, Greece, May 2005.
J. Perkiö, V. Tuulos, W. Buntine, H. Tirri, Multi-Faceted Information Retrieval System for Large Scale Email Archives. Pp. 557-564 in Proceedings of the IEEE/WIC/ACM Conference on Web Intelligence (WI 2005).
J. Perkiö, W. Buntine, and H. Tirri, A Temporally Adaptive Content-Based Relevance Ranking Algorithm. Pp. 647-648 in Proceedings of the Twenty-Eighth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2005).
V. Tuulos, T. Silander, Language Pragmatics, Contexts and a Search Engine in Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (Espoo, Finland, June 2005).
P. Kontkanen, P. Myllymäki, A Fast Normalized Maximum Likelihood Algorithm for Multinomial Data. Pp. 1613-1616 in Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI-05).
P. Kontkanen, P. Myllymäki, Computing the regret table for multinomial data. Helsinki Institute for Information Technology HIIT, Helsinki 2005 (HIIT Technical Report 2005-1).
S. Kaski, P. Myllymäki, and I. Kojo: User models from implicit feedback for proactive information retrieval. In C. de la Higuera and T. Artieres, editors, Proceedings of Workshop 4 of the 10th International Conference on User Modeling; Machine Learning for User Modeling: Challenges, pages 25-26. 2005
M. Miettinen, V. Tuulos, P. Myllymäki, A Testbed for Proactive Information Retrieval. Pp. 137-146 in Proceedings of the Workshop on Context Awareness for Proactive Systems (CAPS 2005), edited by P. Floreen, G. Linden, T. Niklander and K. Raatikainen. Helsinki Institute for Information Technology HIIT, Helsinki 2005 (HIIT Publications 2005-1).
M. Miettinen, P. Nokelainen, J. Kurhila, H. Tirri, Evaluating the Effect of Social Cues with Automated Experiments. Elektrotechnik & Informationstechnik, Vol. 122, No. 12, pp. 477-481.
M. Miettinen, J. Kurhila, H. Tirri, On the Prospects of Intelligent Collaborative E-learning Systems. Pp. 483-490 in the Proceedings of the 12th International Conference on Artificial Intelligence in Education. IOS Press.
M. Miettinen, J. Kurhila, P. Nokelainen, H. Tirri, OurWeb - Transparent Groupware for Online Communities. Pp. 53-61 in the Proceedings of the IADIS International Conference on Web-Based Communities 2005. Algarve, Portugal, February 2005.
P. Nokelainen, M. Miettinen, J. Kurhila, P. Floréen, H. Tirri, A Shared Document-Based Annotation Tool to Support Learner-Centered Collaborative Learning. British Journal of Educational Technology, Vol. 36, No. 5, 757-770.
M. Miettinen, P. Nokelainen, J. Kurhila, T. Silander, H. Tirri, EDUFORM - A Tool for Creating Adaptive Questionnaires. International Journal on E-Learning, Vol. 4 (2005), No. 3, 365-373.
T. Roos, T. Heikkilä, R. Cilibrasi, P. Myllymäki, Compression-based Stemmatology: A Study of the Legend of St. Henry of Finland, Technical Report HIIT-2005-3.
T. Roos, H. Wettig, P. Grünwald, P. Myllymäki, H. Tirri, On Discriminative Bayesian Network Classifiers and Logistic Regression. Machine Learning 59:3, pp. 267-296.
T. Roos, P. Myllymäki, H. Tirri, On the Behavior of MDL Denoising. Pp. 309-316 in Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics (AISTATS), edited by R. Cowell and Z. Ghahramani. Society for Artificial Intelligence and Statistics, 2005.
P. Kontkanen, P. Myllymäki, W. Buntine, J. Rissanen, H. Tirri, An MDL Framework for Data Clustering. In Advances in Minimum Description Length: Theory and Applications, edited by P. Grünwald, I.J. Myung and M. Pitt. The MIT Press, 2005.

2004

W. Hämäläinen, H. Toivonen, and V. Poroshin, Mining relaxed graph properties in internet. IADIS International Conference WWW/Internet 2004, 152-159, Madrid, Spain, October 2004.
W. Buntine, S. Perttu, V. Tuulos, Using Discrete PCA on Web Pages. Pp. 99-110 in Proceedings of the Workshop W1 on Statistical Approaches for Web Mining (SAWM). Edited by M. Gori, M. Ceci and M. Nanni. Pisa, Italy, September 2004.
N. Zhong, H. Tirri, Y. Yao, L. Zhou (eds.), Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (Beijing, China, September 2004). IEEE, 2004.
W. Buntine, J. Löfström, J. Perkiö, S. Perttu, V. Poroshin, T. Silander, H. Tirri, A. Tuominen, V. Tuulos, A Scalable Topic-Based Open Source Search Engine. Pp. 228-234 in Proceedings of the IEEE/WIC/ACM Conference on Web Intelligence (WI 2004).
V. Tuulos, H. Tirri, Combining Topic Models and Social Networks for Chat Data Mining. Pp. 206-213 in Proceedings of the IEEE/WIC/ACM Conference on Web Intelligence (WI 2004).
J. Perkiö, W. Buntine, S. Perttu, Exploring Independent Trends in a Topic-Based Search Engine. Pp. 664-668 in Proceedings of the IEEE/WIC/ACM Conference on Web Intelligence (WI 2004).
W. Buntine, A. Jakulin, Applying Discrete PCA in Data Analysis. Pp. 59-66 in Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence (UAI'04), edited by M. Chickering and J. Halpern. AUAI Press 2004.
J. Kurhila, M. Miettinen, P. Nokelainen, H. Tirri, The Role of the Learning Platform in Student-Centered E-Learning. Pp. 540-544 in the Proceedings of the 4th IEEE International Conference on Advanced Learning Technologies (Joensuu, Finland, August 2004).
G. Lugano, P. Nokelainen, M. Miettinen, J. Kurhila, H. Tirri, On the Relationship Between Learners' Orientations and Activity in CSCL. Pp. 759-761 in the Proceedings of the 4th IEEE International Conference on Advanced Learning Technologies (Joensuu, Finland, August 2004).
E. Savia, S. Kaski, V. Tuulos, P. Myllymaki, On Text-Based Estimation of Document Relevance. Pp. 3275-3280 in Proceedings of the 2004 International Joint Conference on Neural Networks. IEEE, 2004.
P. Kontkanen, P. Myllymäki, T. Roos, H. Tirri, K. Valtonen, H. Wettig, Topics in Probabilistic Location Estimation in Wireless Networks. Invited paper in Proceedings of the 15th IEEE Symposium on Personal, Indoor and Mobile Radio Communications, Barcelona, Spain. IEEE Press, 2004.
P. Kontkanen, P. Myllymäki, T. Roos, H. Tirri, K. Valtonen, H. Wettig, Probabilistic Methods for Location Estimation in Wireless Networks. Chapter 11 in Emerging Location Aware Broadband Wireless Adhoc Networks, edited by R.Ganesh, S.Kota, K.Pahlavan and R.Agustí. Kluwer Academic Publishers, 2004.
P. Nokelainen, H. Tirri, Bayesian Methods that Optimize Cross-cultural Data Analysis. Pp. 141-158 in Cross-cultural Research: Basic Issues, Dilemmas, and Strategies, edited by J.R.Campbell, K. Tirri, P.Ruohotie and H.Walberg. Research Centre for Vocational Education, University of Tampere, Finland, 2004.

2003

J. Rissanen, Complexity and Information in Data, Chapter 15, in ENTROPY, edited by A. Greven, G. Keller, and G. Warnecke. Princeton University Press, Princeton and Oxford, 2003.
J. Kurhila, M. Miettinen, P. Nokelainen, H. Tirri, Enhancing Groupwork with Social Navigation in Collaborative Learning Environment. Pp. 15-23 in Proceedings of the 3rd Annual Finnish/Baltic Sea Conference on Computer Science Education (Joensuu, Finland, October 2003).
J. Kurhila, M. Miettinen, P. Nokelainen, P. Floréen, H. Tirri, Joint Annotation and Knowledge Building in Collaborative E-Learning. Pp. 2249-2252 in Proceedings of the E-Learn 2003 Conference (Phoenix, USA, November 2003).
W. Buntine, P. Myllymäki, S.Perttu, Language Models for Intelligent Search Using Multinomial PCA. Pp. 37-50 in Proceedings of the First European Web Mining Forum at the 14th European Conference on Machine Learning and the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, edited by B. Berendt, A. Hotho, D. Mladenic, M. van Someren. M. Spiliopoulou and G. Stumme. Ruder Boskovic Institute, 2003.
H.Wettig, P. Grünwald, T.Roos, P. Myllymäki, H.Tirri, When Discriminative Learning of Bayesian Network Parameters Is Easy. Pp. 491-496 in Proceedings of the 18th International Joint Conference on Artificial Intelligence, edited by G.Gottlob and T.Walsh. Morgan Kaufmann, 2003.
P.Nokelainen, J.Kurhila, M.Miettinen, P.Floréen, H.Tirri, Evaluating the Role of a Shared Document-based Annotation Tool in Learner-centered Collaborative Learning. Pp. 200-203 in Proceedings of the 3rd IEEE International Conference on Advanced Learning Technologies (Athens, Greece, July 2003).
J.Kurhila, M.Miettinen, P.Nokelainen, P.Floréen, H.Tirri, Peer-To-Peer Learning with Open-Ended Writable Web. Pp. 173-177 in Proceedings of the 8th Annual Conference on Innovation and Technology in Computer Science Education (Thessaloniki, Greece, June 2003).
M.Miettinen, J.Kurhila, P.Nokelainen, P.Floréen, H.Tirri, EDUCOSM - Personalized Writable Web for Learning Communities. Pp. 37-42 in Proceedings of the ITCC 2003 Conference (Las Vegas, USA, April 2003).
P.Nokelainen, P.Ruohotie, M.Miettinen, J.Kurhila, H.Tirri, The role of inservice teachers' motivation, learning strategy and social ability profiles in CSCL. Pp. 1518-1522 in the Proceedings of the SITE 2003 Conference (Albuquergue, USA, March 2003).
J.Rissanen, Complexity of Simple Nonlogarithmic Loss Functions. IEEE Transactions on Information Theory 49 (2003) 2 (February), 476-484.
H.Wettig, J. Lahtinen, T.Lepola, P. Myllymäki, H.Tirri, Bayesian Analysis of Online Newspaper Log Data. Pp. 282-287 in Proceedings of the 2003 Symposium on Applications and the Internet Workshops (SAINT 2003 Workshops). IEEE Computer Society, Los Alamitos, California, 2003.
H.Tirri, Search in vain: challenges for internet search. Pp. 115-116 in Computer, Volume 36, Issue 1, Jan 2003.
P. Kontkanen, W.Buntine, P. Myllymäki, J.Rissanen, H.Tirri, Efficient Computation of Stochastic Complexity. Pp. 181-188 in Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, edited by Christopher M. Bishop and Brendan J. Frey. Society for Artificial Intelligence and Statistics, 2003.
W.Buntine, S.Perttu, Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction?. Pp. 300-307 in Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, edited by C.M. Bishop and B.J. Frey. Society for Artificial Intelligence and Statistics, 2003.
J.Veijalainen, V.Terziyan, H.Tirri. Transaction Management for M-Commerce at a Mobile Terminal, in Proceedings of 36th Hawaii International Conference on Systems Sciences (HICSS-36, Big Island, Hawaii, USA, January 2003).
J.Rousu, L.Flander, M.Suutarinen, K.Autio, P. Kontkanen, A.Rantanen, Novel computational tools in bakery process data analysis: a comparative study. Journal of Food Engineering 57 (2003) 1, 45-56.

2002

H.Wettig, P. Grünwald, T.Roos, P. Myllymäki, H.Tirri, Supervised Naive Bayes Parameters. Pp. 72-83 in STeP 2002 - Intelligence, The Art of Natural and Artificial and Artificial: Proceedings of the 10th Finnish Artificial Intelligence Conference, edited by P. Ala-Siuru and S. Kaski. Finnish Artificial Intelligence Society, 2002.
H.Wettig, P. Grünwald, T.Roos, P. Myllymäki, H.Tirri, Supervised Learning of Bayesian Network Parameters Made Easy. Pp. 95-102 in Proceedings of the 12th Belgian-Dutch Conference on Machine Learning, edited by M. Wiering. Utrecht University, TR UU-CS-2002-046.
P. Kontkanen, P. Myllymäki, W. Buntine, J. Rissanen and H. Tirri: An MDL Framework for Data Clustering. Helsinki Institute for Information Technology HIIT, Helsinki 2002 (HIIT Technical Report 2002-8).
K. Valtonen, T. Mononen, P. Myllymäki, H. Tirri, J. Erkinaro, E. Jokikokko, S. Kuikka, A. Romakkaniemi, L. Karlsson and I. Perä: Predicting the wild salmon production using Bayesian networks. Helsinki Institute for Information Technology HIIT, Helsinki 2002 (HIIT Technical Report 2002-7).
K. Valtonen, T. Mononen, P. Myllymäki, H. Tirri, J. Erkinaro, E. Jokikokko, S. Kuikka, A. Romakkaniemi, L. Karlsson and I. Perä: Cross-analysis of Gulf of Bothnia wild salmon rivers using Bayesian networks. Helsinki Institute for Information Technology HIIT, Helsinki 2002 (HIIT Technical Report 2002-6).
K. Valtonen, T. Mononen, P. Myllymäki, H. Tirri, J. Erkinaro, E. Jokikokko, S. Kuikka and A. Romakkaniemi: A study of electrofishing bias in terms of habitat and abundance using information-theoretic tools. Helsinki Institute for Information Technology HIIT, Helsinki 2002 (HIIT Technical Report 2002-5).
K. Valtonen, Bayesian and Information-Theoretic Modeling for the Wild Salmon (Salmo Salar L) Parr and Smolt Populations of Gulf of Bothnia Rivers. M.Sc. Thesis, Report C-2002-58, Department of Computer Science, University of Helsinki.
A.G. Gray, B. Fischer, J. Schuman, W. Buntine, Automatic Derivation of Statistical Algorithms: The EM Family and Beyond. In Proceedings of Neural Information Processing Systems (NIPS2002, Vancouver, Canada, December 2002).
W. Buntine, S. Perttu, H. Tirri, Building and Maintaining Web Taxonomies. Pp. 54-65 in Towards the Semantic Web and Web Services: Proceedings of XML Finland 2002, edited by E. Hyvönen and M. Klemettinen. HIIT Publications 2002-03.
P. Myllymaki, T. Silander, H. Tirri, P. Uronen, B-Course: A Web-Based Tool for Bayesian and Causal Data Analysis. International Journal on Artificial Intelligence Tools, Vol. 11 (2002), No. 3, 369-387.
J. Kurhila, M. Miettinen, P. Nokelainen, H. Tirri, Enhancing the Sense of Other Learners in Student-Centered Web-Based Education. Pp. 318-322 in Proceedings of the ICCE2002 Conference (Auckland, New Zealand, December 2002).
J. Kurhila, M. Miettinen, P. Nokelainen, H. Tirri, Use of Social Navigation Features in Collaborative E-Learning. Pp. 1738-1741 in Proceedings of the E-Learn 2002 Conference (Montreal, Canada, October 2002).
K. Tirri, E. Komulainen, P. Nokelainen, H. Tirri, Conceptual Modeling of Self-Rated Intelligence-Profile. In Proceedings of 2nd International Self-Concept Research Conference (Sydney, Australia, August 2002).
W. Buntine, H. Tirri, Multi-faceted Learning for Web Taxonomies. Pp. 52-60 in Proceedings of the 2nd Workshop on Semantic Web Mining, edited by A. Hotho and G. Stumme.
K. Virrantaus, J. Markkula, A. Garmash, V. Terziyan, J. Veijalainen, A. Katanosov, H. Tirri, Developing GIS-Supported Location-Based Services. Pp. 66-76 in Proceedings of the Second International Conference on Web Information Systems Engineering. IEEE Computer Society, 2002.
W. Buntine, Variational Extensions to EM and Multinomial PCA. Pp. 23-34 in Proceedings of the 13th European Conference on Machine Learning, edited by T. Elomaa, H. Mannila and H. Toivonen. Vol. 2430 in Lecture Notes in Artificial Intelligence, Springer-Verlag 2002.
P. Nokelainen, J. Kurhila, M. Miettinen, H. Tirri, A Tool for Real Time On-Line Collaboration in Web-Based Learning. Pp. 1448-1453 in Proceedings of the ED-MEDIA 2002 Conference (Denver, USA, June 2002).
J. Kurhila, M. Miettinen, P. Nokelainen, H. Tirri, Dynamic Profiling in a Real-Time Collaborative Learning Environment. Pp. 239-248 in Proceedings of the ITS 2002 Conference (Biarritz, France, June 2002).
P. Nokelainen, H. Tirri. Issues in Designing an Interactive Personalized Self-Assessment Tool. In P.Ruohotie & H.Niemi, Pp. 73-90 in Theoretical understandings for learning in the virtual university. Research Centre for Vocational Education. 2002.
J.Kurhila, M.Miettinen, P.Nokelainen, H.Tirri, EDUCO - A Collaborative Learning Environment Based on Social Navigation. Pp. 242-252 in Proceedings of the 2nd International Conference on Adaptive Hypermedia and Adaptive Web Based Systems (Malaga, Spain, May 2002).
P. Nokelainen, H. Tirri, J. Kurhila, M. Miettinen, T. Silander, Optimizing and profiling users online with Bayesian probabilistic modeling. In Proceedings of The NL 2002 Conference (Berlin, Germany, May 2002).
M. Miettinen, P. Nokelainen, J. Kurhila, T. Silander, H. Tirri, Adaptive Profiling Tool for Teacher Education. Pp. 1153-1157 in Proceedings of the SITE 2002 Conference (Nashville, USA, March 2002). Received the Outstanding Paper Award.
H. Wettig, P. Grünwald, T. Roos, P. Myllymäki, H. Tirri, On Supervised Learning of Bayesian Network Parameters. HIIT Technical Report 2002-1.
P. Grünwald, P. Kontkanen, P. Myllymäki, T. Roos, H. Tirri, H.Wettig, Supervised Posterior Distributions. Presented at the Seventh Valencia International Meeting on Bayesian Statistics, Tenerife, Spain, June 2002.
T. Roos, P. Myllymäki, H. Tirri, P. Misikangas, J. Sievänen, A Probabilistic Approach to WLAN User Location Estimation. International Journal of Wireless Information Networks, Vol. 9, No. 3, July 2002.
T. Roos, P. Myllymäki, H. Tirri, A Statistical Modeling Approach to Location Estimation. IEEE Transactions on Mobile Computing, Vol. 1, No. 1, January-March 2002, 59-69.

2001

Ruohotie, R., Nokelainen, P.,Tirri, H.,Silander, T.Modeling Individual and Organizational Prerequisites of Professional Growth - Papers presented at International Conferences 1999-2001 . Saarijärven Offset, 2001.
Russell S. Thomas, David R. Rank, Sharron G. Penn, Gina M. Zastrow, Kevin R. Hayes, Kalyan Pande, Edward Glover, Tomi Silander, Mark W. Craven, Janardan K. Reddy, Stevan B. Jovanovich, Christopher A. Bradfield Identification of toxicologically predictive gene sets using cDNA microarrays Mol Pharmacol 2001 60: 1189-1194, 2001.
M. Paakko, N. Holsti, P. Myllymäki, H. Tirri, Bayesian Networks for Advanced FDIR. Pp. 311-318 in Proceedings of the ESA Workshop on On-Board Autonomy (Noordwijk, The Netherlands, October 2001). WPP-191, European Space Agency, 2001.
P. Myllymäki, T. Silander, H. Tirri, P. Uronen, Bayesian Data Mining on the Web with B-Course. Pp. 626-629 in Proceedings of The 2001 IEEE International Conference on Data Mining, edited by N. Cercone, T.Y. Lin and X. Wu. IEEE Computer Society Press, 2001.
P. Myllymäki, T. Silander, H. Tirri, P. Uronen, B-Course: A Web Service for Bayesian Data Analysis. Pp. 247-256 in Proceedings of The Thirteenth IEEE International Conference on Tools with Artificial Intelligence, edited by R.Bilof and L.Palagi. IEEE Computer Society Press, 2001.
P. Myllymäki, T. Roos, H. Tirri, P. Misikangas, J. Sievänen, A Probabilistic Approach to WLAN User Location Estimation. In Proceedings of The Third IEEE Workshop on Wireless Local Areas Networks (Boston, USA, September 2001).
P. Kontkanen, P. Myllymäki, H. Tirri, Classifier Learning with Supervised Marginal Likelihood. Pp. 277- 284 in Proceedings of the 17th International Conference on Uncertainty in Artificial Intelligence (UAI'01), edited by J.Breese and D.Koller. Morgan Kaufmann Publishers, 2001.
H. Tirri, Designing B-Course: observations from educational point of view (http://b-course.cs.helsinki.fi). In IJCAI'01 workshop on Effective Interactive AI Resources, Seattle, August 2001.
P. Kontkanen, P. Myllymäki, H. Tirri, Comparing Prequential Model Selection Criteria in Supervised Learning of Mixture Model. Pp. 233-238 in Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, edited by T.Jaakkola and T.Richardson. Morgan Kaufmann Publishers, 2001.
J. Kurhila, M. Miettinen, M. Niemivirta, P. Nokelainen, T. Silander, H. Tirri Bayesian Modeling in an Adaptive On-Line Questionnaire for Education and Educational Research . Pp. 194-201 in Proceedings of The 10th International PEG2001 Conference , Tampere, June 2001.
P. Nokelainen, T. Silander, H. Tirri, K. Tirri, A. Nevgi Modeling Students' Views on the Advantages of Web-Based Learning with Bayesian Networks . Pp. 202-211 in Proceedings of The 10th International PEG2001 Conference , Tampere, June 2001.
P. Nokelainen, M. Niemivirta, J. Kurhila, M. Miettinen, T. Silander, H. Tirri Implementation of an Adaptive Questionnaire . In Proceedings of Ed-Media Conference , Tampere, June 2001.
T. Tonteri, A Statistical Modeling Approach to Location Estimation. Master's Thesis, Dept. of Computer Science, University of Helsinki, May 2001.

2000

T. Silander and H. Tirri, Model Selection for Bayesian Networks. In Proceedings of the Annual American Educational Research Association Meeting (AERA'00), SIG Educational Statisticians, New Orleans, 2000.
H. Tirri, T. Silander and P. Uronen, B-Course - a free Bayesian data analysis service. Proceedings of the NIPS'2000 Workshop on Software Support for Bayesian Analysis Systems. RIACS, NASA Ames Reseach Center, December 2000.
P. Kontkanen, J. Lahtinen, P. Myllymäki, T. Silander, and H. Tirri, Supervised Model-Based Visualization of High-Dimensional Data. Intelligent Data Analysis 4 (2000), 213-227.
P. Kontkanen, P. Myllymäki, H. Tirri and K. Valtonen, Bayesian Multinet Classifiers. In Proceedings of The 10th International Conference on Computing and Information (ICCI'2000). Kuwait, November 2000.
P. Kontkanen, J. Lahtinen, P. Myllymäki, and H. Tirri, An Unsupervised Bayesian Distance Measure. Pp. 148-160 in Advances in Case-Based Reasoning, Proceedings of the Fifth European Workshop on Case-Based Reasoning (EWCBR-2000), edited by E.Blanzieri and L.Portinale. Vol. 1898 in Lecture Notes in Artificial Intelligence, Springer-Verlag 2000.
P. Kontkanen, J. Lahtinen, P. Myllymäki, and H. Tirri, Unsupervised Bayesian Visualization of High-Dimensional Data. Pp. 325-329 in Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining (KDD-2000), edited by R.Ramakrishnan, S.Stolfo, R.Bayardo and I.Parsa. The Association for Computing Machinery, New York, NY, USA, 2000.
P. Kontkanen, P. Myllymäki, H. Tirri and K. Valtonen, Classification with Bayesian Multinets. Pp. 134-146 in Proceedings of TOOLMET-2000, Symposium on Tool Environments and Development Methods for Intelligent Systems, edited by L.Yliniemi and E.Juuso. Oulun Yliopistopaino, 2000.
P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, and P. Grünwald, On Predictive Distributions and Bayesian Networks. Statistics and Computing 10 (2000), 39-54.

1999

P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Density Estimation by Minimum Encoding Mixtures of Histograms. Pp. 162-164 in Book of Abstracts, Second European Conference on Highly Structured Stochastic Systems (HSSS'99), Pavia, Italy, September 1999.
P. Myllymäki, Massively Parallel Probabilistic Reasoning with Boltzmann Machines. Applied Intelligence 11, 31-44 (1999).
P. Kontkanen, J. Lahtinen, P. Myllymäki, T. Silander, and H. Tirri, Using Bayesian Networks for Visualizing High-Dimensional Data. Pp. 38-47 in Proceedings of Pre- and Post-processing in Machine Learning and Data Mining: Theoretical Aspects and Applications, a workshop within Machine Learning and Applications (ACAI-99), edited by I.Bruha. Chania, Greece, July 1999.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Urban Legends in Bayesian Network Research I: Model Selection for Supervised Problems. Arpakannus 1/99, 8-14.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, On the Accuracy of Stochastic Complexity Approximations. Chapter 9 in Causal Models and Intelligent Data Management, edited by A.Gammerman. Springer-Verlag, 1999.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, On Supervised Selection of Bayesian Networks. Pp. 334-342 in Proceedings of the 15th International Conference on Uncertainty in Artificial Intelligence (UAI'99), edited by K. Laskey and H. Prade. Morgan Kaufmann Publishers, 1999.
J. Lahtinen, P. Myllymäki, T. Silander, H. Tirri, and H.Wettig, An Empirical Evaluation of Stochastic Search Methods in Real-World Telecommunication Domains. Pp. 181-187 in Proceedings of the 3rd World Multiconference on Systemics, Cybernetics and Informatics (SCI'99) and 5th International Conference on Information Systems Analysis and Synthesis (ISAS'99), Volume 4, edited by M. Torres, B. Sanchez, S. Radhakrishan and R. Osers. International Institute of Information and Systemics, 1999.
P.Ruohotie, H. Tirri, P.Nokelainen and T. Silander, Modern Modeling of Professional Growth. Research Center for Vocational Education, Saarijärven Offset 1999.
H. Tirri, What the heritage of Thomas Bayes has to offer for modern educational research? Chapter II in P.Ruohotie, H. Tirri, P.Nokelainen and T. Silander, Modern Modeling of Professional Growth. Research Center for Vocational Education, Saarijärven Offset 1999.
T. Silander and H. Tirri, Bayesian classification. Chapter III in P.Ruohotie, H. Tirri, P.Nokelainen and T. Silander, Modern Modeling of Professional Growth. Research Center for Vocational Education, Saarijärven Offset 1999.
P. Nokelainen, P. Ruohotie and H. Tirri, Professional Growth Determinants-Comparing Bayesian and linear approaches to classification. Chapter IV in P.Ruohotie, H. Tirri, P.Nokelainen and T. Silander, Modern Modeling of Professional Growth. Research Center for Vocational Education, Saarijärven Offset 1999.
P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, K.Valtonen, Exploring the Robustness of Bayesian and Information-Theoretic Methods for Predictive Inference. Pp. 231-236 in Proceedings of Uncertainty'99: The Seventh International Workshop on Artificial Intelligence and Statistics, edited by D.Heckerman and J.Whittaker. Morgan Kaufmann Publishers, 1999.

1998

P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, On Bayesian Case Matching. Pp. 13-24 in Advances in Case-Based Reasoning, Proceedings of the 4th European Workshop (EWCBR-98), edited by B.Smyth and P.Cunningham. Vol. 1488 in Lecture Notes in Artificial Intelligence, Springer-Verlag, 1998.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, BAYDA: Software for Bayesian Classification and Feature Selection. Pp. 254-258 in Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining (KDD-98), edited by R.Agrawal, P.Stolorz and G.Piatetsky-Shapiro. AAAI Press, Menlo Park, CA, 1998.
P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, and P. Grünwald, On the Small Sample Size Behavior of Bayesian and Information-Theoretic Approaches for Predictive Inference. Presented at the 6th Valencia International Meeting on Bayesian Statistics, Alcossebre, Spain, May-June 1998.
P. Grünwald, P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Minimum Encoding Approaches for Predictive Modeling. Pp. 183-192 in Proceedings of the 14th International Conference on Uncertainty in Artificial Intelligence (UAI'98), edited by G.Cooper and S.Moral. Morgan Kaufmann Publishers, San Francisco, CA, 1998.
E. Koskimäki, J. Göös, P. Kontkanen, P. Myllymäki, and H. Tirri, Comparing Soft Computing Methods in Prediction of Manufacturing Data. Pp. 775-784 in Tasks and Methods in Applied Artificial Intelligence, Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA-98-AIE), edited by A.P. del Pobil, J.Mira and M. Ali. Vol. 1416 in Lecture Notes in Artificial Intelligence, Springer-Verlag, 1998.
H. Tirri and T. Silander, Stochastic complexity based estimation of missing elements in questionnaire data. Presented at the Annual American Educational Research Association Meeting (AERA'98), SIG Educational Statisticians, San Diego, 1998.
P. Myllymäki and H. Tirri, Prospects of Bayesian networks (in Finnish). Technology Report 58/98. Technology Development Center (TEKES), 1998.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Bayes Optimal Instance-Based Learning. Pp. 77-88 in Machine Learning: ECML-98, Proceedings of the 10th European Conference, edited by C.Nédellec and C.Rouveirol. Vol. 1398 in Lecture Notes in Artificial Intelligence, Springer-Verlag, 1998.
P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, and P. Grünwald, Bayesian and Information-Theoretic Priors for Bayesian Network Parameters. Pp. 89-94 in Machine Learning: ECML-98, Proceedings of the 10th European Conference, edited by C.Nédellec and C.Rouveirol. Vol. 1398 in Lecture Notes in Artificial Intelligence, Springer-Verlag, 1998.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Batch Classifications with Discrete Finite Mixtures. Pp. 208-213 in Machine Learning: ECML-98, Proceedings of the 10th European Conference, edited by C.Nédellec and C.Rouveirol. Vol. 1398 in Lecture Notes in Artificial Intelligence, Springer-Verlag, 1998.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Bayesian Classification and Feature Selection with BAYDA. In ECML-98: Demonstration and poster papers, edited by C.Nédellec and C.Rouveirol. CSR-98-07, Technische Universität Chemnitz, 1998.
P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, and P. Grünwald, A Comparison of non-informative priors for Bayesian networks. Pp. 53-62 in The Yearbook of the Finnish Statistical Society 1997, Hakapaino Oy, Helsinki 1998.

1997

P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, and P. Grünwald, Bayesian and Information-Theoretic Predictive Distributions for Bayesian Networks. Pp. 59-68 in Proceedings of the Seventh Belgian-Dutch Conference on Machine Learning (BeNeLearn '97), edited by W. Daelemans, P. Flach and A. van den Bosch. Tilburg, the Netherlands, October 1997.
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, A Bayesian Approach for Retrieving Relevant Cases. Pp. 67-72 in Artificial Intelligence Applications (Proceedings of the EXPERSYS-97 Conference), edited by P.Smith. IITT International, Gournay sur Marne, 1997.
H. Tirri, T. Silander and K. Tirri, Using neural networks for descriptive statistical analysis of educational data. Presented at the Annual American Educational Research Association Meeting (AERA'97), SIG Educational Statisticians, Chigago, 1997.
H. Tirri, T. Silander and K. Tirri, Bayesian Finite Mixtures for nonlinear modeling of educational data. Presented at the Annual American Educational Research Association Meeting (AERA'97), Division D, Chigago, 1997.
H. Tirri, Plausible Prediction by Bayesian Inference. Ph.D. Dissertation, Report A-1997-1, Department of Computer Science, University of Helsinki, June 1997.
P. Kontkanen, P. Myllymäki, and H. Tirri, Experimenting with the Cheeseman-Stutz Evidence Approximation for Predictive Modeling and Data Mining. Pp. 204-211 in Proceedings the Tenth International FLAIRS Conference (Daytona Beach, Florida, May 1997).
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, A Bayesian Approach to Discretization. Pp. 265-268 in Proceedings of the European Symposium on Intelligent Techniques (Bari, Italy, March 1997).
P. Kontkanen, P. Myllymäki, T. Silander, and H. Tirri, Comparing Stochastic Complexity Minimization Algorithms in Estimating Missing Data. Pp. 81-90 in Proceedings of WUPES'97, the 4th Workshop on Uncertainty Processing (Prague, Czech Republic, January 1997).
P. Kontkanen, P. Myllymäki, T. Silander, H. Tirri, and P. Grünwald, Comparing Predictive Inference Methods for Discrete Domains. Pp. 311-318 in Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics (Ft. Lauderdale, USA, January 1997).

1996

H. Tirri, P. Kontkanen, and P. Myllymäki, A Bayesian Framework for Case-Based Reasoning. Pp. 413-427 in Advances in Case-Based Reasoning (Proceedings of the 3rd European Workshop), edited by I.Smith and B.Faltings. Lecture Notes in Artificial Intelligence, Volume 1168, Springer-Verlag, Berlin Heidelberg, 1996.
J. Lahtinen, P. Myllymäki, T. Silander, and H. Tirri, Empirical comparison of stochastic algorithms in a graph optimization problem. Pp. 45-59 in Proceedings of the Second Nordic Workshop on Genetic Algorithms and their Applications (Vaasa, Finland, August 1996), edited by J.Alander. University of Vaasa and the Finnish Artificial Intelligence Society, Vaasa, 1996.
P. Kontkanen, P. Myllymäki and H. Tirri, Predictive Data Mining with Finite Mixtures. Pp. 176-182 in Proceedings of The Second International Conference on Knowledge Discovery and Data Mining (Portland, OR, August 1996).
P. Kontkanen, P. Myllymäki and H. Tirri, Comparing Bayesian model class selection criteria by discrete finite mixtures. Pp. 364-374 in Information, Statistics and Induction in Science(Proceedings of the ISIS'96 Conference in Melbourne, Australia, August 1996), edited by D.L.Dowe, K.B.Korb, and J.J.Oliver. World Scientific , Singapore 1996.
P. Kontkanen, P. Myllymäki and H. Tirri, Constructing Bayesian finite mixture models by the EM algorithm. NeuroCOLT Technical Report NC-TR-97-003.
H. Tirri, P. Kontkanen and P. Myllymäki, Probabilistic Instance-Based Learning. Pp. 507-515 in Machine Learning: Proceedings of the Thirteenth International Conference, edited by L. Saitta. Morgan Kaufmann Publishers, San Francisco, CA, 1996.
P. Kontkanen, P. Myllymäki and H. Tirri, Some experimental results with finite mixture models. Pp. 112-115 in Proceedings of the First European Conference on Highly Structured Stochastic Systems (Rebild, Denmark, May 1996).
P. Orponen, The computational power of discrete Hopfield nets with hidden units. Neural Computation 8 (1996), 403-415.
R. Greiner, P. Orponen, Probably approximately optimal satisficing strategies. Artificial Intelligence 82 (1996), 21-44.
H. Buhrman, P. Orponen, Random strings make hard instances. J. Comput. System Sciences 53 (1996), 261-266.

1995

P. Myllymäki, Mapping Bayesian Networks to Stochastic Neural Networks: A Foundation for Hybrid Bayesian-Neural Systems. Ph.D. Dissertation, Report A-1995-1, Department of Computer Science, University of Helsinki, December 1995.
H. Tirri and S.Mallenius, Optimizing the Hard Address Distribution for Sparse Distributed Memories. Pp. 1966-1970 in Proceedings of the IEEE International Conference on Neural Networks (Perth, November 1995).
X.M.Song, H. Tirri, O.Aaltonen and A.Hase, A Discrete Radial Basis Function Network for Empirical Modeling of Soil Extraction Process. Pp. 17-20 in Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN'95), 1995.
P. Myllymäki, Mapping Bayesian Networks to Boltzmann Machines . Pp. 269-280 in Proceedings of Applied Decision Technologies 1995 (London, April 1995).
H. Tirri, Replacing the Pattern Matching of an Expert System with a Neural Network. Pp. 47-62 in Intelligent Hybrid Systems, edited by S. Goonatilake and S. Khebbal. John Wiley & Sons, Chichester 1995.
P. Myllymäki and H. Tirri, Constructing computationally efficient Bayesian models via unsupervised clustering. Pp. 237-248 in Probabilistic Reasoning and Bayesian Belief Networks, edited by A.Gammerman. Alfred Waller Publishers, Suffolk 1995.

1994

P. Orponen, Computational complexity of neural networks: A survey. Nordic Journal of Computing 1 (1994), 94-110.
P. Floréen, J. N. Kok, M. N. Rasch, Three methods for tracing a simple genetic algorithm. Pp. 148-158 in Proceedings of the 4th Belgian-Dutch Conference on Machine Learning (Benelearn 94, Rotterdam, June 1994), edited by J. C. Bioch and S. H. Nienhuys-Cheng. Erasmus University Rotterdam Report EUR-CS-94-05, Rotterdam 1994.
P. Floréen and J.N.Kok, Tracing the moments of distributions in genetic algorithms. Pp. 51-60 in Proceedings of the Second Finnish Workshop on Genetic Algorithms and their Applications (Vaasa, Finland, March 1994), edited by J.T. Alander. Report 94-2, University of Vaasa, 1994.
P. Myllymäki and H. Tirri, Learning Bayesian prototype trees by simulated annealing. Pp. 32-37 in Proceedings of the Conference on Artificial Intelligence Research in Finland (Turku, Finland, August 1994), edited by C.Carlsson, T.Järvi and T.Reponen. Finnish Artificial Intelligence Society, Helsinki 1994.
P. Myllymäki and H. Tirri, Massively parallel case-based reasoning with probabilistic similarity metrics. Pp. 144-154 in Topics in Case-Based Reasoning, edited by S.Wess, K.-D.Althoff and M.Richter. Lecture Notes in Artificial Intelligence, Volume 837. Springer Verlag, 1994.
P. Orponen, K. Ko, U. Schöning, O. Watanabe, Instance complexity. J. Assoc. Comput. Mach. 41 (1994), 96-121.
P. Floréen and T. Huuskonen, Uniqueness of maximum values in discrete distributions. Journal of Applied Probability 31 (September 1994).
H. Tirri and P. Myllymäki, MDL learning of probabilistic neural networks for discrete problem domains. Pp. 1493-1497 in Proceedings of the IEEE World Congress on Computational Intelligence (Orlando, June 1994).
P. Myllymäki and H. Tirri, Learning in neural networks with Bayesian prototypes. Pp. 60-64 in Proceedings of SOUTHCON'94 (Orlando, March 1994).
P. Myllymäki, Using Bayesian networks for incorporating probabilistic a priori knowledge into Boltzmann machines. Pp. 97-102 in Proceedings of SOUTHCON'94 (Orlando, March 1994).
S. Santos, Phase transitions in sparsely connected Boltzmann machines. Report C-1994-15, Department of Computer Science, University of Helsinki, 1994.

1993

P. Myllymäki, Bayesian reasoning by stochastic neural networks. Ph.Lic. Thesis, Report C-1993-67, Department of Computer Science, University of Helsinki, 1993.
P. Floréen, A short introduction to neural associative memories. Bulletin of the European Association for Theoretical Computer Science 51 (October 1993), 236-245.
P. Orponen, On the computational power of discrete Hopfield nets. Pp.215-226 in Proc. 20th Internat. Colloq. on Automata, Languages, and Programming (Lund, Sweden, July 1993). Lecture Notes in Computer Science 700, Springer-Verlag, Berlin Heidelberg, 1993.
P. Myllymäki and H. Tirri, Bayesian case-based reasoning with neural networks. Pp. 422-427 in Proceedings of the IEEE International Conference on Neural Networks (San Francisco, March 1993).
P. Floréen and P. Orponen, Attraction radii in binary Hopfield nets are hard to compute. Neural Computation 5 (1993), 812-821.

1992

P. Floréen, Computational complexity problems in neural associative memories. Ph. D. Thesis, Report A-1992-5, Department of Computer Science, University of Helsinki, 1992.
P. Floréen, Neuraaliset assosiatiivimuistit. Tietojenkäsittelytiede 3 (1992), 44-47.
P. Floréen, P. Myllymäki, P. Orponen, and H. Tirri, Neula: A hybrid neural-symbolic expert system shell. Tietojenkäsittelytiede 3 (1992), 11-18.
P. Floréen, A new associative memory model. International Journal of Intelligent Systems 7 (1992), 455-467.
P. Orponen, Neural networks and complexity theory (invited talk). Pp. 50-61 in Proc. of the 17th Internat. Symp. on Mathematical Foundations of Computer Science (Prague, Czechoslovakia, August 1992). Lecture Notes in Computer Science 629, Springer-Verlag, Berlin Heidelberg, 1992.
P. Myllymäki, P. Orponen, and T. Silander, Integrating symbolic reasoning with neurally represented background knowledge. Pp. 231-240 in Proceedings of the Finnish AI Conference (Espoo, Finland, June 1992), edited by E. Hyvönen, J. Seppänen and M. Syrjänen. Finnish AI Society, Helsinki, 1992.

1991

P. Myllymäki and P. Orponen, Programming the harmonium. Pp. 671-677 in Proceedings of the International Joint Conference on Neural Networks (Singapore, November 1991).
P. Floréen, Worst-case convergence times for Hopfield memories. IEEE Transactions on Neural Networks 2 (1991), 533-535.
P. Floréen, The convergence of Hamming memory networks. IEEE Transactions on Neural Networks, 2 (1991),449-457.
H. Tirri, Concept randomness and neural networks. Pp. 1367-1370 in Proceedings of the International Conference on Artificial Neural Networks (Espoo, Finland, June 1991), edited by T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas. Elsevier Science Publishers, Amsterdam 1991.

1990

H. Tirri, Implementing Expert System Rule Conditions by Neural Networks. New Generation Computing 10 (1991), 55-71. Also: TR-1050, Department of Computer Sciences, Purdue University, 1990.
P. Floréen, P. Myllymäki, P. Orponen, and H. Tirri, Compiling object declarations into connectionist networks. AI Communications 3 (1990) 4 (December), 172-183.
P. Floréen, Computational complexity issues in neural associative memories. Ph.Lic Thesis, Report C-1990-40, Department of Computer Science, University of Helsinki, 1990.
R.J.T. Morris, L.D. Rubin, and H. Tirri, Neural network techniques for object orientation detection: Solution by optimal feedforward network and learning vector quantization approaches. IEEE Transactions on Pattern Analysis and Machine Intelligence 12 (1990) 11 (November), 1107-1115.
P. Orponen, P. Floréen, P. Myllymäki, and H. Tirri, A neural implementation of conceptual hierarchies with Bayesian reasoning. Pp. 297-303 in Proceedings of the International Joint Conference on Neural Networks (San Diego, CA, June 1990). IEEE, New York, 1990.
P. Floréen, An analysis of the convergence time of Hamming memory networks. Pp. 867-872 in Proceedings of the International Joint Conference on Neural Networks (San Diego, CA, June 1990). IEEE, New York, 1990.
P. Orponen, P. Floréen, P. Myllymäki, and H. Tirri, A neural implementation of Bayesian reasoning. Pp. 277-287 in Proceedings of the Finnish Artificial Intelligence Symposium (Oulu, Finland, June 1990), edited by P. Salonen M. Djupsund and M. Syrjänen. Finnish Artificial Intelligence Society, 1990.
P. Myllymäki, H. Tirri, P. Floréen, and P. Orponen, Compiling high-level specifications into neural networks. Pp. 475-478 in Proceedings of the International Joint Conference on Neural Networks (Washington D.C., January 1990). IEEE, New York, 1990.
P. Orponen, Dempster's rule of combination is #P-complete. Artificial Intelligence 44 (1990), 245-253.

1989

P. Floréen and P. Orponen, On the computational complexity of analyzing Hopfield nets. Complex Systems 3 (1989), 577-587.
P. Floréen, P. Myllymäki, P. Orponen, and H. Tirri, Neural representation of concepts for robust inference. Pp. 89-98 in Proceedings of the International Symposium Computational Intelligence II (Milano, Italy, September 1989), edited by F. Gardin and G. Mauri. Elsevier Science Publishers, Amsterdam, 1989.
H. Tirri, Applying neural computing to expert system design. Part I: Coping with complex sensory data and attribute selection. Pp. 474-488 in Proceedings of the 3rd International Conference on Data Organization and Algorithms (Paris, France, June 1989) edited by W. Litwin and H.-J. Schek. Springer-Verlag, Berlin Heidenberg, 1989.
H. Tirri, Neural information processing and applications. Tutorial at the 3rd International Conference on Data Organization and Algorithms (Paris, France, June 1989). Institut National de Recherche en Informatique et en Automatique (INRIA), Le Chesnay Cedex, France, 1989.
P. Orponen, An experimental evaluation of the optimal capacity of the Hopfield associative memory. Page 612 in Proceedings of the International Joint Conference on Neural Networks (Washington, D.C., June 1989). IEEE, New York, 1989.
P. Floréen and P. Orponen, Counting stable states and sizes of attraction domains in Hopfield nets is hard. Pp. 395-399 in Proceedings of the International Joint Conference on Neural Networks (Washington, D.C, June 1989). IEEE, New York, 1989.
R.J.T. Morris, L.D. Rubin, and H. Tirri, A comparison of feedforward and self-organizing approaches to the font orientation problem. Pp. 291-298 in Proceedings of the International Joint Conference on Neural Networks (Washington, D.C., June 1989). IEEE, New York, 1989.
H. Tirri, Feedforward and learning vector quantization approaches for font orientation detection. In Nordic Symposium on Neural Computing (Hanasaari, Finland, April 1989).

Last updated on 23 Dec 2017 by Teemu Roos - Page created on 18 Sep 2012 by Petri Myllymäki

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