Pedro M. Domingos

According to our database1, Pedro M. Domingos authored at least 153 papers between 1994 and 2018.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

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 Convex-Combinatorial Optimization Problem.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
On the Latent Variable Interpretation in Sum-Product 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 Sum-Product 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 High-Speed Data Streams, 2016

2015
Learning and Inference in Tractable Probabilistic Knowledge Bases.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Recursive Decomposition for Nonconvex Optimization - IJCAI-15 Distinguished Paper.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

On Theoretical Properties of Sum-Product Networks.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Learning Relational Sum-Product Networks.
Proceedings of the Twenty-Ninth 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 Twenty-Eighth 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 Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Learning the Structure of Sum-Product 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 Sum-Product 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 3-6, 2012

Knowledge Extraction and Joint Inference Using Tractable Markov Logic.
Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction, 2012

A Tractable First-Order Probabilistic Logic.
Proceedings of the Twenty-Sixth 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

Sum-Product 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

Sum-product networks: A new deep architecture.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Formula-Based 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 6-9 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 6-9 December 2010, 2010

Learning Markov Logic Networks Using Structural Motifs.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Bottom-Up Learning of Markov Network Structure.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 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 Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

Efficient Belief Propagation for Utility Maximization and Repeated Inference.
Proceedings of the Twenty-Fourth 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

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 second-order 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 Twenty-Third AAAI Conference on Artificial Intelligence, 2008

Lifted First-Order Belief Propagation.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Toward knowledge-rich 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 Twenty-Second 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

Memory-Efficient 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 Attribute-Mediated Dependences.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Collective Object Identification.
Proceedings of the IJCAI-05, 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

Real-World 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

Real-World 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 multi-relational data mining.
SIGKDD Explorations, 2003

Tree Induction for Probability-Based 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 (K-CAP 2003), 2003

Learning programs from traces using version space algebra.
Proceedings of the 2nd International Conference on Knowledge Capture (K-CAP 2003), 2003

Automatically Personalizing User Interfaces.
Proceedings of the IJCAI-03, 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 KDD-2001 Panel.
SIGKDD Explorations, 2002

Learning to map between ontologies on the semantic web.
Proceedings of the Eleventh International World Wide Web Conference, 2002

Mining knowledge-sharing 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 Machine-Learning 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 time-changing 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

2000
Learning Source Description for Data Integration.
Proceedings of the Third International Workshop on the Web and Databases, 2000

Mining high-speed 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 Bias-Variance 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: Process-Oriented Evaluation.
Proceedings of the Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31, 2000

A Unified Bias-Variance Decomposition for Zero-One 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 Cost-Sensitive.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

Process-Oriented Estimation of Generalization Error.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Process-oriented 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 (KDD-98), 1998

A Process-Oriented 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 Zero-One Loss.
Machine Learning, 1997

Control-Sensitive 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 (KDD-97), 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 Instance-Based and Rule-Based Induction.
Machine Learning, 1996

Efficient Specific-to-General Rule Induction.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Linear-Time Rule Induction.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 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 Instance-Based Learning: A Unified Approach.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

Progressive rules: a method for representing and using real-time knowledge.
Proceedings of the Seventh International Conference on Tools with Artificial Intelligence, 1995

Two-way 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


  Loading...