Pedro M. Domingos
According to our database^{1},
Pedro M. Domingos
authored at least 158 papers
between 1994 and 2019.
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at id.loc.gov

at dl.acm.org
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Bibliography
2019
Unifying logical and statistical AI with Markov logic.
Commun. ACM, 2019
2018
Machine Learning for Data Management: Problems and Solutions.
Proceedings of the 2018 International Conference on Management of Data, 2018
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Deep Learning as a Mixed ConvexCombinatorial Optimization Problem.
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
On the Latent Variable Interpretation in SumProduct Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2017
Compositional Kernel Machines.
Proceedings of the 5th International Conference on Learning Representations, 2017
2016
Unifying Logical and Statistical AI.
Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer Science, 2016
The SumProduct Theorem: A Foundation for Learning Tractable Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Learning Tractable Probabilistic Models for Fault Localization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
Mining Decision Trees from Streams.
Proceedings of the Data Stream Management  Processing HighSpeed Data Streams, 2016
2015
Learning and Inference in Tractable Probabilistic Knowledge Bases.
Proceedings of the ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
Recursive Decomposition for Nonconvex Optimization  IJCAI15 Distinguished Paper.
Proceedings of the TwentyFourth International Joint Conference on Artificial Intelligence, 2015
On Theoretical Properties of SumProduct Networks.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
Learning Relational SumProduct Networks.
Proceedings of the TwentyNinth AAAI Conference on Artificial Intelligence, 2015
2014
Deep Symmetry Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Exchangeable Variable Models.
Proceedings of the 31th International Conference on Machine Learning, 2014
Approximate Lifting Techniques for Belief Propagation.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
Tractable Probabilistic Knowledge Bases: Wikipedia and Beyond.
Proceedings of the Statistical Relational Artificial Intelligence, 2014
Learning Tractable Statistical Relational Models.
Proceedings of the Statistical Relational Artificial Intelligence, 2014
Automated Debugging with Tractable Probabilistic Programming.
Proceedings of the Statistical Relational Artificial Intelligence, 2014
2013
Structured Message Passing.
Proceedings of the TwentyNinth Conference on Uncertainty in Artificial Intelligence, 2013
Learning the Structure of SumProduct Networks.
Proceedings of the 30th International Conference on Machine Learning, 2013
Tractable Probabilistic Knowledge Bases with Existence Uncertainty.
Proceedings of the Statistical Relational Artificial Intelligence, 2013
2012
A few useful things to know about machine learning.
Commun. ACM, 2012
Discriminative Learning of SumProduct Networks.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
Knowledge Extraction and Joint Inference Using Tractable Markov Logic.
Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Webscale Knowledge Extraction, 2012
A Tractable FirstOrder Probabilistic Logic.
Proceedings of the TwentySixth AAAI Conference on Artificial Intelligence, 2012
2011
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning.
Machine Learning, 2011
Deep Transfer: A Markov Logic Approach.
AI Magazine, 2011
SumProduct Networks: A New Deep Architecture.
Proceedings of the UAI 2011, 2011
Probabilistic Theorem Proving.
Proceedings of the UAI 2011, 2011
Approximation by Quantization.
Proceedings of the UAI 2011, 2011
Implementing Weighted Abduction in Markov Logic.
Proceedings of the Ninth International Conference on Computational Semantics, 2011
Sumproduct networks: A new deep architecture.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011
CoarsetoFine Inference and Learning for FirstOrder Probabilistic Models.
Proceedings of the TwentyFifth AAAI Conference on Artificial Intelligence, 2011
2010
FormulaBased Probabilistic Inference.
Proceedings of the UAI 2010, 2010
Approximate Inference by Compilation to Arithmetic Circuits.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
Learning Efficient Markov Networks.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
Learning Markov Logic Networks Using Structural Motifs.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
BottomUp Learning of Markov Network Structure.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
Unsupervised Ontology Induction from Text.
Proceedings of the ACL 2010, 2010
Approximate Lifted Belief Propagation.
Proceedings of the Statistical Relational Artificial Intelligence, 2010
Machine Reading: A "Killer App" for Statistical Relational AI.
Proceedings of the Statistical Relational Artificial Intelligence, 2010
Efficient Lifting for Online Probabilistic Inference.
Proceedings of the Statistical Relational Artificial Intelligence, 2010
Efficient Lifting for Online Probabilistic Inference.
Proceedings of the TwentyFourth AAAI Conference on Artificial Intelligence, 2010
Efficient Belief Propagation for Utility Maximization and Repeated Inference.
Proceedings of the TwentyFourth AAAI Conference on Artificial Intelligence, 2010
Using Structural Motifs for Learning Markov Logic Networks.
Proceedings of the Statistical Relational Artificial Intelligence, 2010
Leveraging Ontologies for Lifted Probabilistic Inference and Learning.
Proceedings of the Statistical Relational Artificial Intelligence, 2010
Exploiting Logical Structure in Lifted Probabilistic Inference.
Proceedings of the Statistical Relational Artificial Intelligence, 2010
Markov Logic: A Language and Algorithms for Link Mining.
Proceedings of the Link Mining: Models, Algorithms, and Applications, 2010
2009
Markov Logic: An Interface Layer for Artificial Intelligence
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, 2009
Learning Markov logic network structure via hypergraph lifting.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Deep transfer via secondorder Markov logic.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Unsupervised Semantic Parsing.
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009
2008
Structured machine learning: the next ten years.
Machine Learning, 2008
Learning Arithmetic Circuits.
Proceedings of the UAI 2008, 2008
Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition.
Proceedings of the Structural, 2008
Just Add Weights: Markov Logic for the Semantic Web.
Proceedings of the Uncertainty Reasoning for the Semantic Web I, 2008
Extracting Semantic Networks from Text Via Relational Clustering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008
Markov Logic.
Proceedings of the Probabilistic Inductive Logic Programming  Theory and Applications, 2008
Joint Unsupervised Coreference Resolution with Markov Logic.
Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, 2008
Markov logic: a unifying language for knowledge and information management.
Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008
Hybrid Markov Logic Networks.
Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence, 2008
Lifted FirstOrder Belief Propagation.
Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence, 2008
A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC.
Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence, 2008
2007
Toward knowledgerich data mining.
Data Min. Knowl. Discov., 2007
Markov Logic in Infinite Domains.
Proceedings of the UAI 2007, 2007
Efficient Weight Learning for Markov Logic Networks.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007
Recursive Random Fields.
Proceedings of the IJCAI 2007, 2007
Statistical predicate invention.
Proceedings of the Machine Learning, 2007
Markov Logic in Infinite Domains.
Proceedings of the Probabilistic, Logical and Relational Learning  A Further Synthesis, 15.04., 2007
Joint Inference in Information Extraction.
Proceedings of the TwentySecond AAAI Conference on Artificial Intelligence, 2007
2006
Markov logic networks.
Machine Learning, 2006
Learning, Logic, and Probability: A Unified View.
Proceedings of the PRICAI 2006: Trends in Artificial Intelligence, 2006
Entity Resolution with Markov Logic.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006
Learning, Logic, and Probability: A Unified View.
Proceedings of the Advances in Artificial Intelligence, 2006
Learning, Logic, and Probability: A Unified View.
Proceedings of the Managing Knowledge in a World of Networks, 2006
MemoryEfficient Inference in Relational Domains.
Proceedings of the Proceedings, 2006
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies.
Proceedings of the Proceedings, 2006
Unifying Logical and Statistical AI.
Proceedings of the Proceedings, 2006
2005
Social Networks Applied.
IEEE Intelligent Systems, 2005
Reports on the 2005 AAAI Spring Symposium Series.
AI Magazine, 2005
Object Identification with AttributeMediated Dependences.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005
Collective Object Identification.
Proceedings of the IJCAI05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005
Naive Bayes models for probability estimation.
Proceedings of the Machine Learning, 2005
Learning the structure of Markov logic networks.
Proceedings of the Machine Learning, 2005
An Efficient and Scalable Architecture for Neural Networks with Backpropagation Learning.
Proceedings of the 2005 International Conference on Field Programmable Logic and Applications (FPL), 2005
Organizing Committee.
Proceedings of the Knowledge Collection from Volunteer Contributors, 2005
Discriminative Training of Markov Logic Networks.
Proceedings of the Proceedings, 2005
2004
iMAP: Discovering Complex Mappings between Database Schemas.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2004
RealWorld Learning with Markov Logic Networks.
Proceedings of the Knowledge Discovery in Databases: PKDD 2004, 2004
Adversarial classification.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004
Learning, Logic, and Probability: A Unified View.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004
Learning Bayesian network classifiers by maximizing conditional likelihood.
Proceedings of the Machine Learning, 2004
RealWorld Learning with Markov Logic Networks.
Proceedings of the Machine Learning: ECML 2004, 2004
Learning, Logic, and Probability: A Unified View.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004
Combining Link and Content Information in Web Search.
Proceedings of the Web Dynamics  Adapting to Change in Content, Size, Topology and Use, 2004
Ontology Matching: A Machine Learning Approach.
Proceedings of the Handbook on Ontologies, 2004
2003
Learning to match ontologies on the Semantic Web.
VLDB J., 2003
Prospects and challenges for multirelational data mining.
SIGKDD Explorations, 2003
Tree Induction for ProbabilityBased Ranking.
Machine Learning, 2003
Programming by Demonstration Using Version Space Algebra.
Machine Learning, 2003
Learning to Match the Schemas of Data Sources: A Multistrategy Approach.
Machine Learning, 2003
Trust Management for the Semantic Web.
Proceedings of the Semantic Web, 2003
Building large knowledge bases by mass collaboration.
Proceedings of the 2nd International Conference on Knowledge Capture (KCAP 2003), 2003
Learning programs from traces using version space algebra.
Proceedings of the 2nd International Conference on Knowledge Capture (KCAP 2003), 2003
Automatically Personalizing User Interfaces.
Proceedings of the IJCAI03, 2003
Learning with Knowledge from Multiple Experts.
Proceedings of the Machine Learning, 2003
Learning from Networks of Examples.
Proceedings of the Progress in Artificial Intelligence, 2003
2002
When and How to Subsample: Report on the KDD2001 Panel.
SIGKDD Explorations, 2002
Learning to map between ontologies on the semantic web.
Proceedings of the Eleventh International World Wide Web Conference, 2002
Mining knowledgesharing sites for viral marketing.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002
Mining complex models from arbitrarily large databases in constant time.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002
Relational Markov models and their application to adaptive web navigation.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002
Representing and Reasoning about Mappings between Domain Models.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002
2001
Personalizing Web Sites for Mobile Users.
Proceedings of the Tenth International World Wide Web Conference, 2001
Reconciling Schemas of Disparate Data Sources: A MachineLearning Approach.
Proceedings of the 2001 ACM SIGMOD international conference on Management of data, 2001
The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
Learning from Infinite Data in Finite Time.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
Mining timechanging data streams.
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001
Mining the network value of customers.
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001
Mixed initiative interfaces for learning tasks: SMARTedit talks back.
Proceedings of the 6th International Conference on Intelligent User Interfaces, 2001
Adaptive Web Navigation for Wireless Devices.
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001
Catching up with the Data: Research Issues in Mining Data Streams.
Proceedings of the 2001 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 2001
Learning Repetitive TextEditing Procedures with SMARTedit.
Proceedings of the Your Wish is My Command, 2001
2000
Learning Source Description for Data Integration.
Proceedings of the Third International Workshop on the Web and Databases, 2000
Mining highspeed data streams.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000
Version Space Algebra and its Application to Programming by Demonstration.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
A Unifeid BiasVariance Decomposition and its Applications.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
Bayesian Averaging of Classifiers and the Overfitting Problem.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
Beyond Occam's Razor: ProcessOriented Evaluation.
Proceedings of the Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31, 2000
A Unified BiasVariance Decomposition for ZeroOne and Squared Loss.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000
1999
The Role of Occam's Razor in Knowledge Discovery.
Data Min. Knowl. Discov., 1999
MetaCost: A General Method for Making Classifiers CostSensitive.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999
ProcessOriented Estimation of Generalization Error.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999
Processoriented evaluation: The next step.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999
1998
Knowledge Discovery Via Multiple Models.
Intell. Data Anal., 1998
Occam's Two Razors: The Sharp and the Blunt.
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD98), 1998
A ProcessOriented Heuristic for Model Selection.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998
1997
On the Optimality of the Simple Bayesian Classifier under ZeroOne Loss.
Machine Learning, 1997
ControlSensitive Feature Selection for Lazy Learners.
Artif. Intell. Rev., 1997
Why Does Bagging Work? A Bayesian Account and its Implications.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD97), 1997
Knowledge Acquisition form Examples Vis Multiple Models.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997
Learning Multiple Models without Sacrificing Comprehensibility.
Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997
A Comparison of Model Averaging Methods in Foreign Exchange Prediction.
Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997
1996
Unifying InstanceBased and RuleBased Induction.
Machine Learning, 1996
Efficient SpecifictoGeneral Rule Induction.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD96), 1996
LinearTime Rule Induction.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD96), 1996
Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier.
Proceedings of the Machine Learning, 1996
Simple Bayesian Classifiers Do Not Assume Independence.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996
Multistrategy Learning: A Case Study.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996
Fast Discovery of Simple Rules.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996
Towards a Unified Approach to Concept Learning.
Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996
1995
Rule Induction and InstanceBased Learning: A Unified Approach.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995
Progressive rules: a method for representing and using realtime knowledge.
Proceedings of the Seventh International Conference on Tools with Artificial Intelligence, 1995
Twoway induction.
Proceedings of the Seventh International Conference on Tools with Artificial Intelligence, 1995
1994
The RISE System: Conquering without Separating.
Proceedings of the Sixth International Conference on Tools with Artificial Intelligence, 1994