Friedman, Nir

58 publications

ICML 2010 Continuous-Time Belief Propagation Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman

JMLR 2010 Mean Field Variational Approximation for Continuous-Time Bayesian Networks Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman

UAI 2009 Convexifying the Bethe Free Energy Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman

UAI 2009 Mean Field Variational Approximation for Continuous-Time Bayesian Networks Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman

UAI 2008 Gibbs Sampling in Factorized Continuous-Time Markov Processes Tal El-Hay, Nir Friedman, Raz Kupferman

JMLR 2007 "Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks Gal Elidan, Iftach Nachman, Nir Friedman

UAI 2007 Template Based Inference in Symmetric Relational Markov Random Fields Ariel Jaimovich, Ofer Meshi, Nir Friedman

UAI 2006 Continuous Time Markov Networks Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman

UAI 2006 Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks Nir Friedman, Raz Kupferman

JMLR 2005 Learning Hidden Variable Networks: The Information Bottleneck Approach Gal Elidan, Nir Friedman

JMLR 2005 Learning Module Networks Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman

UAI 2004 "Ideal Parent" Structure Learning for Continuous Variable Networks Iftach Nachman, Gal Elidan, Nir Friedman

MLJ 2003 Being Bayesian About Network Structure. a Bayesian Approach to Structure Discovery in Bayesian Networks Nir Friedman, Daphne Koller

UAI 2003 Learning Module Networks Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman

UAI 2003 The Information Bottleneck EM Algorithm Gal Elidan, Nir Friedman

AAAI 2002 Data Perturbation for Escaping Local Maxima in Learning Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans

JMLR 2002 Learning Probabilistic Models of Link Structure Lisa Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar

UAI 2002 UAI '02, Proceedings of the 18th Conference in Uncertainty in Artificial Intelligence, University of Alberta, Edmonton, Alberta, Canada, August 1-4, 2002 Adnan Darwiche, Nir Friedman

NeurIPS 2001 Agglomerative Multivariate Information Bottleneck Noam Slonim, Nir Friedman, Naftali Tishby

UAI 2001 Incorporating Expressive Graphical Models in VariationalApproximations: Chain-Graphs and Hidden Variables Tal El-Hay, Nir Friedman

ICML 2001 Learning Probabilistic Models of Relational Structure Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar

UAI 2001 Learning the Dimensionality of Hidden Variables Gal Elidan, Nir Friedman

UAI 2001 Multivariate Information Bottleneck Nir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby

UAI 2000 Being Bayesian About Network Structure Nir Friedman, Daphne Koller

NeurIPS 2000 Discovering Hidden Variables: A Structure-Based Approach Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller

UAI 2000 Gaussian Process Networks Nir Friedman, Iftach Nachman

UAI 2000 Likelihood Computations Using Value Abstraction Nir Friedman, Dan Geiger, Noam Lotner

UAI 1999 Data Analysis with Bayesian Networks: A Bootstrap Approach Nir Friedman, Moisés Goldszmidt, Abraham J. Wyner

UAI 1999 Discovering the Hidden Structure of Complex Dynamic Systems Xavier Boyen, Nir Friedman, Daphne Koller

AISTATS 1999 Efficient Learning Using Constrained Sufficient Statistics Nir Friedman, Lise Getoor

UAI 1999 Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm Nir Friedman, Iftach Nachman, Dana Pe'er

IJCAI 1999 Learning Probabilistic Relational Models Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer

UAI 1999 Model Based Bayesian Exploration Richard Dearden, Nir Friedman, David Andre

JAIR 1999 Modeling Belief in Dynamic Systems, Part II: Revision and Update Nir Friedman, Joseph Y. Halpern

ICML 1998 Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting Nir Friedman, Moisés Goldszmidt, Thomas J. Lee

AAAI 1998 Bayesian Q-Learning Richard Dearden, Nir Friedman, Stuart Russell

AAAI 1998 Belief Revision with Unreliable Observations Craig Boutilier, Nir Friedman, Joseph Y. Halpern

NeurIPS 1998 Efficient Bayesian Parameter Estimation in Large Discrete Domains Nir Friedman, Yoram Singer

UAI 1998 Learning the Structure of Dynamic Probabilistic Networks Nir Friedman, Kevin P. Murphy, Stuart Russell

AAAI 1998 Structured Representation of Complex Stochastic Systems Nir Friedman, Daphne Koller, Avi Pfeffer

UAI 1998 The Bayesian Structural EM Algorithm Nir Friedman

MLJ 1997 Bayesian Network Classifiers Nir Friedman, Dan Geiger, Moisés Goldszmidt

IJCAI 1997 Challenge: What Is the Impact of Bayesian Networks on Learning? Nir Friedman, Moisés Goldszmidt, David Heckerman, Stuart Russell

NeurIPS 1997 Generalized Prioritized Sweeping David Andre, Nir Friedman, Ronald Parr

UAI 1997 Image Segmentation in Video Sequences: A Probabilistic Approach Nir Friedman, Stuart Russell

ICML 1997 Learning Belief Networks in the Presence of Missing Values and Hidden Variables Nir Friedman

UAI 1997 Sequential Update of Bayesian Network Structure Nir Friedman, Moisés Goldszmidt

UAI 1996 A Qualitative Markov Assumption and Its Implications for Belief Change Nir Friedman, Joseph Y. Halpern

AAAI 1996 Building Classifiers Using Bayesian Networks Nir Friedman, Moisés Goldszmidt

UAI 1996 Context-Specific Independence in Bayesian Networks Craig Boutilier, Nir Friedman, Moisés Goldszmidt, Daphne Koller

ICML 1996 Discretizing Continuous Attributes While Learning Bayesian Networks Nir Friedman, Moisés Goldszmidt

AAAI 1996 First-Order Conditional Logic Revisited Nir Friedman, Joseph Y. Halpern, Daphne Koller

UAI 1996 Learning Bayesian Networks with Local Structure Nir Friedman, Moisés Goldszmidt

UAI 1996 On the Sample Complexity of Learning Bayesian Networks Nir Friedman, Zohar Yakhini

AAAI 1996 Plausibility Measures and Default Reasoning Nir Friedman, Joseph Y. Halpern

IJCAI 1995 On Decision-Theoretic Foundations for Defaults Ronen I. Brafman, Nir Friedman

UAI 1995 Plausibility Measures: A User's Guide Nir Friedman, Joseph Y. Halpern

AAAI 1994 Conditional Logics of Belief Change Nir Friedman, Joseph Y. Halpern