Publications » Complex Systems Computation Group CoSCo

Selected Publications of CoSCo Group

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2002

• A.G.Gray, B.Fischer, J.Schuman, W.Buntine, Automatic Derivation of Statistical Algorithms: The EM Family and Beyond. To appear in Proceedings of Neural Information Processing Systems (NIPS2002, Vancouver, Canada, Dec. 2002).
• W.Buntine, S.Perttu, H.Tirri, Building and Maintaining Web Taxonomies. Pp. 54-65 in Proceedings of XML Finland 2002 (Helsinki, Finland, October 2002).
• 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. To appear 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. To appear in Proceedings of the E-Learn 2002 Conference (Montreal, Canada, October 2002).
• W.Buntine, H.Tirri, Multi-faceted Learning for Web Taxonomies. Pp. 52-60 in Proceedings of the 2nd Workshop on Semantic Web Mining (ECML2002, Helsinki, Finland, August 2002).
• 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 (Helsinki, Finland, August 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).
• 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).
• 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

• 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 HREF="http://cosco.hiit.fi/Articles/toxi.pdf"> 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. To appear 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. To appear 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).

University of Helsinki | Department of Computer Science | Helsinki Institute for Information Technology

cosco@hiit.fi