Domingos, Pedro M

71 publications

NeurIPS 2018 Submodular Field Grammars: Representation, Inference, and Application to Image Parsing Abram L. Friesen, Pedro M Domingos

ICLR 2017 Compositional Kernel Machines Robert Gens, Pedro M. Domingos

AAAI 2016 Learning Tractable Probabilistic Models for Fault Localization Aniruddh Nath, Pedro M. Domingos

AAAI 2015 Learning Relational Sum-Product Networks Aniruddh Nath, Pedro M. Domingos

UAI 2015 Learning and Inference in Tractable Probabilistic Knowledge Bases Mathias Niepert, Pedro M. Domingos

AISTATS 2015 On Theoretical Properties of Sum-Product Networks Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos

IJCAI 2015 Recursive Decomposition for Nonconvex Optimization - IJCAI-15 Distinguished Paper Abram L. Friesen, Pedro M. Domingos

AAAI 2014 Approximate Lifting Techniques for Belief Propagation Parag Singla, Aniruddh Nath, Pedro M. Domingos

NeurIPS 2014 Deep Symmetry Networks Robert Gens, Pedro M Domingos

UAI 2013 Structured Message Passing Vibhav Gogate, Pedro M. Domingos

AAAI 2012 A Tractable First-Order Probabilistic Logic Pedro M. Domingos, William Austin Webb

UAI 2011 Approximation by Quantization Vibhav Gogate, Pedro M. Domingos

AAAI 2011 Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models Chloé Kiddon, Pedro M. Domingos

MLJ 2011 Guest Editorial to the Special Issue on Inductive Logic Programming, Mining and Learning in Graphs and Statistical Relational Learning Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan

UAI 2011 Probabilistic Theorem Proving Vibhav Gogate, Pedro M. Domingos

UAI 2011 Sum-Product Networks: A New Deep Architecture Hoifung Poon, Pedro M. Domingos

ICML 2010 Bottom-up Learning of Markov Network Structure Jesse Davis, Pedro M. Domingos

AAAI 2010 Efficient Belief Propagation for Utility Maximization and Repeated Inference Aniruddh Nath, Pedro M. Domingos

AAAI 2010 Efficient Lifting for Online Probabilistic Inference Aniruddh Nath, Pedro M. Domingos

UAI 2010 Formula-Based Probabilistic Inference Vibhav Gogate, Pedro M. Domingos

ICML 2010 Learning Markov Logic Networks Using Structural Motifs Stanley Kok, Pedro M. Domingos

ICML 2009 Deep Transfer via Second-Order Markov Logic Jesse Davis, Pedro M. Domingos

ICML 2009 Learning Markov Logic Network Structure via Hypergraph Lifting Stanley Kok, Pedro M. Domingos

AAAI 2008 A General Method for Reducing the Complexity of Relational Inference and Its Application to MCMC Hoifung Poon, Pedro M. Domingos, Marc Sumner

ECML-PKDD 2008 Extracting Semantic Networks from Text via Relational Clustering Stanley Kok, Pedro M. Domingos

AAAI 2008 Hybrid Markov Logic Networks Jue Wang, Pedro M. Domingos

UAI 2008 Learning Arithmetic Circuits Daniel Lowd, Pedro M. Domingos

AAAI 2008 Lifted First-Order Belief Propagation Parag Singla, Pedro M. Domingos

MLJ 2008 Structured Machine Learning: The Next Ten Years Thomas G. Dietterich, Pedro M. Domingos, Lise Getoor, Stephen H. Muggleton, Prasad Tadepalli

AAAI 2007 Joint Inference in Information Extraction Hoifung Poon, Pedro M. Domingos

UAI 2007 Markov Logic in Infinite Domains Parag Singla, Pedro M. Domingos

IJCAI 2007 Recursive Random Fields Daniel Lowd, Pedro M. Domingos

ICML 2007 Statistical Predicate Invention Stanley Kok, Pedro M. Domingos

MLJ 2006 Markov Logic Networks Matthew Richardson, Pedro M. Domingos

AAAI 2006 Memory-Efficient Inference in Relational Domains Parag Singla, Pedro M. Domingos

AAAI 2006 Sound and Efficient Inference with Probabilistic and Deterministic Dependencies Hoifung Poon, Pedro M. Domingos

AAAI 2006 Unifying Logical and Statistical AI Pedro M. Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla

IJCAI 2005 Collective Object Identification Parag Singla, Pedro M. Domingos

AAAI 2005 Discriminative Training of Markov Logic Networks Parag Singla, Pedro M. Domingos

ICML 2005 Learning the Structure of Markov Logic Networks Stanley Kok, Pedro M. Domingos

ICML 2005 Naive Bayes Models for Probability Estimation Daniel Lowd, Pedro M. Domingos

ICML 2004 Learning Bayesian Network Classifiers by Maximizing Conditional Likelihood Daniel Grossman, Pedro M. Domingos

ALT 2004 Learning, Logic, and Probability: A Unified View Pedro M. Domingos

ECML-PKDD 2004 Real-World Learning with Markov Logic Networks Pedro M. Domingos

IJCAI 2003 Automatically Personalizing User Interfaces Daniel S. Weld, Corin R. Anderson, Pedro M. Domingos, Oren Etzioni, Krzysztof Gajos, Tessa A. Lau, Steven A. Wolfman

MLJ 2003 Learning to Match the Schemas of Data Sources: A Multistrategy Approach AnHai Doan, Pedro M. Domingos, Alon Y. Halevy

ICML 2003 Learning with Knowledge from Multiple Experts Matthew Richardson, Pedro M. Domingos

MLJ 2003 Programming by Demonstration Using Version Space Algebra Tessa A. Lau, Steven A. Wolfman, Pedro M. Domingos, Daniel S. Weld

MLJ 2003 Tree Induction for Probability-Based Ranking Foster J. Provost, Pedro M. Domingos

AAAI 2002 Representing and Reasoning About Mappings Between Domain Models Jayant Madhavan, Philip A. Bernstein, Pedro M. Domingos, Alon Y. Halevy

ICML 2001 A General Method for Scaling up Machine Learning Algorithms and Its Application to Clustering Pedro M. Domingos, Geoff Hulten

IJCAI 2001 Adaptive Web Navigation for Wireless Devices Corin R. Anderson, Pedro M. Domingos, Daniel S. Weld

ICML 2000 A Unifeid Bias-Variance Decomposition and Its Applications Pedro M. Domingos

AAAI 2000 A Unified Bias-Variance Decomposition for Zero-One and Squared Loss Pedro M. Domingos

ICML 2000 Bayesian Averaging of Classifiers and the Overfitting Problem Pedro M. Domingos

ECML-PKDD 2000 Beyond Occam's Razor: Process-Oriented Evaluation Pedro M. Domingos

ICML 2000 Version Space Algebra and Its Application to Programming by Demonstration Tessa A. Lau, Pedro M. Domingos, Daniel S. Weld

IJCAI 1999 Process-Oriented Estimation of Generalization Error Pedro M. Domingos

AISTATS 1999 Process-Oriented Evaluation: The Next Step Pedro M. Domingos

ICML 1998 A Process-Oriented Heuristic for Model Selection Pedro M. Domingos

AAAI 1997 A Comparison of Model Averaging Methods in Foreign Exchange Prediction Pedro M. Domingos

ICML 1997 Knowledge Acquisition Form Examples Vis Multiple Models Pedro M. Domingos

AAAI 1997 Learning Multiple Models Without Sacrificing Comprehensibility Pedro M. Domingos

MLJ 1997 On the Optimality of the Simple Bayesian Classifier Under Zero-One Loss Pedro M. Domingos, Michael J. Pazzani

ICML 1996 Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier Pedro M. Domingos, Michael J. Pazzani

AAAI 1996 Fast Discovery of Simple Rules Pedro M. Domingos

AAAI 1996 Multistrategy Learning: A Case Study Pedro M. Domingos

AAAI 1996 Simple Bayesian Classifiers Do Not Assume Independence Pedro M. Domingos, Michael J. Pazzani

AAAI 1996 Towards a Unified Approach to Concept Learning Pedro M. Domingos

MLJ 1996 Unifying Instance-Based and Rule-Based Induction Pedro M. Domingos

IJCAI 1995 Rule Induction and Instance-Based Learning: A Unified Approach Pedro M. Domingos