Myllymäki, Petri

27 publications

MLJ 2018 Empirical Hardness of Finding Optimal Bayesian Network Structures: Algorithm Selection and Runtime Prediction Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki

UAI 2015 Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical Evaluation Brandon M. Malone, Matti Järvisalo, Petri Myllymäki

AAAI 2014 Optimal Neighborhood Preserving Visualization by Maximum Satisfiability Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen, Samuel Kaski

AAAI 2014 Predicting the Hardness of Learning Bayesian Networks Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki

AISTATS 2014 Robust Learning of Inhomogeneous PMMs Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse

ACML 2013 Achievability of Asymptotic Minimax Regret in Online and Batch Prediction Kazuho Watanabe, Teemu Roos, Petri Myllymäki

JMLR 2011 Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood Alexandra M. Carvalho, Teemu Roos, Arlindo L. Oliveira, Petri Myllymäki

AISTATS 2009 Locally Minimax Optimal Predictive Modeling with Bayesian Networks Tomi Silander, Teemu Roos, Petri Myllymäki

UAI 2008 UAI 2008, Proceedings of the 24th Conference in Uncertainty in Artificial Intelligence, Helsinki, Finland, July 9-12, 2008 David A. McAllester, Petri Myllymäki

AISTATS 2007 MDL Histogram Density Estimation Petri Kontkanen, Petri Myllymäki

UAI 2007 On Sensitivity of the MAP Bayesian Network Structure to the Equivalent Sample Size Parameter Tomi Silander, Petri Kontkanen, Petri Myllymäki

UAI 2006 A Simple Approach for Finding the Globally Optimal Bayesian Network Structure Tomi Silander, Petri Myllymäki

IJCAI 2005 A Fast Normalized Maximum Likelihood Algorithm for Multinomial Data Petri Kontkanen, Petri Myllymäki

NeurIPS 2005 Generalization to Unseen Cases Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri

MLJ 2005 On Discriminative Bayesian Network Classifiers and Logistic Regression Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri

AISTATS 2005 On the Behavior of MDL Denoising Teemu Roos, Petri Myllymäki, Henry Tirri

AISTATS 2003 Efficient Computing of Stochastic Complexity Petri Kontkanen, Wray L. Buntine, Petri Myllymäki, Jorma Rissanen, Henry Tirri

IJCAI 2003 When Discriminative Learning of Bayesian Network Parameters Is Easy Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri

UAI 2001 Classifier Learning with Supervised Marginal Likelihood Petri Kontkanen, Petri Myllymäki, Henry Tirri

AISTATS 2001 Comparing Prequential Model Selection Criteria in Supervised Learning of Mixture Models Petri Kontkanen, Petri Myllymäki, Henry Tirri

UAI 1999 On Supervised Selection of Bayesian Networks Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri

ECML-PKDD 1998 Batch Classification with Discrete Finite Mixtures Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri

ECML-PKDD 1998 Bayes Optimal Instance-Based Learning Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri

ECML-PKDD 1998 Bayesian and Information-Theories Priors for Bayesian Network Parameters Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald

UAI 1998 Minimum Encoding Approaches for Predictive Modeling Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri

AISTATS 1997 Comparing Predictive Inference Methods for Discrete Domains Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald

ICML 1996 Prababilistic Instance-Based Learning Henry Tirri, Petri Kontkanen, Petri Myllymäki