Machine Learning
2013
Structured sparse learning of multiple Gaussian graphical model
K. Mohan, M. Chung, S. Han, D. Witten, S.I. Lee, M. Fazel, Advances in Neural Information Processing Systems (NIPS), 2013.
2012
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
M.M. Hoffman, O.J. Buske, J. Wang, Z. Weng, J.A. Bilmes, W.S. Noble, Nature Methods 9:5, 2012.
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Faster Mass Spectrometry-based Protein Inference: Junction Trees are More Efficient than Sampling and Marginalization by Enumeration.
O. Serang, W.S. Noble, IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM, 2012.
Epigenetic priors for identifying active transcription factor binding sites.
G. Cuellar-Partida, F.A. Buske, R.C. McLeay, T. Whitington, W.S. Noble, T.L. Bailey, Bioinformatics (Oxford, England) 28:1, 2012.
Direct maximization of protein identifications from tandem mass spectra.
M. Spivak, J. Weston, D. Tomazela, M.J. MacCoss, W.S. Noble, Molecular & cellular proteomics : MCP 11:2, 2012.
A unified multitask architecture for predicting local protein properties.
Y. Qi, M. Oja, J. Weston, W.S. Noble, PloS one 7:3, 2012.
A Few Useful Things to Know about Machine Learning
P. Domingos, Communications of the ACM 55:10, 2012.
A Tractable First-Order Probabilistic Logic
P. Domingos, A. Webb, Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012.
Counting-MLNs: Learning Relational Structure for Decision Making
A. Nath, M. Richardson, AAAI Conference on Artificial Intelligence, 2012.
Integrative annotation of chromatin elements from ENCODE data
M.M. Hoffman, J. Ernst, S.P. Wilder, A. Kundaje, R.S. Harris, M. Libbrecht, B. Giardine, P.M. Ellenbogen, J.A. Bilmes, E. Birney, R.C. Hardison, I. Dunham, M. Kellis, W.S. Noble, Nucleic Acids Research In Press, 2012.
Learning Multiple Hierarchical Relational Clusterings
A. Nath, P. Domingos, ICML-12 Workshop on Statistical Relational Learning, 2012.
ReGroup: Interactive Machine Learning for On-Demand Group Creation in Social Networks
S. Amershi, J. Fogarty, D.S. Weld, Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI-12), 2012.
2011
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
C. Kiddon, P. Domingos, AAAI Conference on Artificial Intelligence, 2011.
Identifying Relations for Open Information Extraction
A. Fader, S. Soderland, O. Etzioni, Conference on Empirical Methods in Natural Language Processing, 2011.
Open Information Extraction: the Second Generation
O. Etzioni, A. Fader, J. Christensen, S. Soderland, Mausam, International Joint Conference on Artificial Intelligence, 2011.
Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
R. Hoffmann, C. Zhang, X. Ling, L. Zettlemoyer, D. Weld, Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2011.
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Inference Over the Web
S. Schoenmackers, PHD Thesis, 2011.
Implementing Weighted Abduction in Markov Logic
J. Blythe, J. Hobbs, P. Domingos, R. Kate, R. Mooney, International Conference on Computational Semantics, 2011.
Faster SEQUEST searching for peptide identification from tandem mass spectra.
B.J. Diament, W.S. Noble, Journal of proteome research 10:9, 2011.
Approximation by Quantization
V. Gogate, P. Domingos, Uncertainty in Artificial Intelligence, 2011.
Probabilistic Theorem Proving
V. Gogate, P. Domingos, Uncertainty in Artificial Intelligence, 2011.
Sum-Product Networks: A New Deep Architecture
H. Poon, P. Domingos, Uncertainty in Artificial Intelligence, 2011.
2010
A Latent Dirichlet Allocation method for Selectional Preferences
A. Ritter, Mausam, O. Etzioni, Annual Meeting of the Association for Computational Linguistics, 2010.
Approximate Lifted Belief Propagation
P. Singla, A. Nath, P. Domingos, Workshop on Statistical Relational AI, 2010.
Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models
D. Wyatt, T. Choudhury, J. Bilmes, AAAI Conference on Artificial Intelligence, 2010.
Efficient Belief Propagation for Utility Maximization and Repeated Inference
A. Nath, P. Domingos, AAAI Conference on Artificial Intelligence, 2010.
Exploiting Logical Structure in Lifted Probabilistic Inference
V. Gogate, P. Domingos, Workshop on Statistical Relational AI, 2010.
Extracting Sequences from the Web
A. Fader, S. Soderland, O. Etzioni, Annual Meeting of the Association for Computational Linguistics, 2010.
Formula-Based Probabilistic Inference
V. Gogate, P. Domingos, Uncertainty in Artificial Intelligence, 2010.
Learning 5000 Relational Extractors
R. Hoffmann, D. Weld, Annual Meeting of the Association for Computational Linguistics, 2010.
Leveraging Ontologies for Lifted Probabilistic Inference and Learning
C. Kiddon, P. Domingos, Workshop on Statistical Relational AI, 2010.
Machine Reading: A "Killer App" for Statistical Relational AI
H. Poon, P. Domingos, Workshop on Statistical Relational AI, 2010.
Open Information Extraction using Wikipedia
F. Wu, D. Weld, Annual Meeting of the Association for Computational Linguistics, 2010.
Panlingual Lexical Translation via Probabilistic Inference
Mausam, S. Soderland, O. Etzioni, AAAI Conference on Artificial Intelligence, 2010.
Bottom-Up Learning of Markov Network Structure
J. Davis, P. Domingos, International Conference on Machine Learning, 2010.
Learning Markov Logic Networks Using Structural Motifs
S. Kok, P. Domingos, International Conference on Machine Learning, 2010.
Machine Reading at the University of Washington
H. Poon, J. Christensen, P. Domingos, O. Etzioni, R. Hoffmann, C. Kiddon, Mausam, A. Ritter, S. Soderland, D. Weld, F. Wu, T. Lin, X. Ling, S. Schoenmackers, Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2010.
Semantic Role Labeling for Open Information Extraction
Mausam, S. Soderland, O. Etzioni, J. Christensen, Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2010.
Approximate Inference by Compilation to Arithmetic Circuits
D. Lowd, P. Domingos, Annual Conference on Neural Information Processing Systems, 2010.
Learning Efficient Markov Networks
V. Gogate, W. Webb, P. Domingos, Annual Conference on Neural Information Processing Systems, 2010.
Lifted Inference Seen from the Other Side: The Tractable Features
A. Jha, V. Gogate, A. Meliou, D. Suciu, Annual Conference on Neural Information Processing Systems, 2010.
Commonsense from the Web: Relation Properties
T. Lin, Mausam, O. Etzioni, AAAI Fall Symposium Series, 2010.
Identifying Functional Relations in Web Text
T. Lin, Mausam, O. Etzioni, Conference on Empirical Methods in Natural Language Processing, 2010.
Learning First-Order Horn Clauses from Web Text
S. Schoenmackers, J. Davis, O. Etzioni, D. Weld, Conference on Empirical Methods in Natural Language Processing, 2010.
Analysis of a Probabilistic Model of Redundancy in Unsupervised Information Extraction
O. Etzioni, S. Soderland, D. Downey, Artificial Intelligence 174:11, 2010.
Twin Gaussian Processes for Structured Prediction
L. Bo, C. Sminchisescu, International Journal of Computer Vision, 2010.
2009
A Rose is a Roos is a Ruusu: Querying Translations for Web Image Search
J. Christensen, Mausam, O. Etzioni, Annual Meeting of the Association for Computational Linguistics, 2009.
Compiling a Massive, Multilingual Dictionary via Probabilistic Inference
Mausam, S. Soderland, O. Etzioni, D. Weld, M. Skinner, J. Bilmes, Annual Meeting of the Association for Computational Linguistics, 2009.
Lemmatic Machine Translation
S. Soderland, Mausam, O. Etzioni, C. Lim, J. Pool, B. Qin, Machine Translation Summit, 2009.
Unsupervised Semantic Parsing
H. Poon, P. Domingos, Conference on Empirical Methods in Natural Language Processing, 2009.
A Language for Relational Decision Theory
A. Nath, P. Domingos, International Workshop on Statistical Relational Learning, 2009.
Deep Transfer via Second-Order Markov Logic
J. Davis, P. Domingos, International Conference on Machine Learning, 2009.
Amplifying Community Content Creation with Mixed Initiative Information Extraction
R. Hoffmann, S. Amershi, K. Patel, F. Wu, J. Fogarty, D. Weld, Conference on Human Factors in Computing Systems, 2009.
Collective Modeling of Human Social Behavior
D. Wyatt, AAAI Spring Symposium Series, 2009.
What Is This, Anyway: Automatic Hypernym Discovery
A. Ritter, S. Soderland, O. Etzioni, AAAI Spring Symposium Series, 2009.
Conditional Neural Fields
J. Peng, L. Bo, J. Xu, Annual Conference on Neural Information Processing Systems, 2009.
Dynamic Multi-Valued Network Models for Predicting Face-to-Face Conversations
D. Wyatt, J. Bilmes, T. Choudhury, Annual Conference on Neural Information Processing Systems, 2009.
Efficient Match Kernels between Sets of Features for Visual Recognition
L. Bo, C. Sminchisescu, Annual Conference on Neural Information Processing Systems, 2009.
Identifying Interesting Assertions from the Web
T. Lin, O. Etzioni, J. Fogarty, ACM Conference on Information and Knowledge Management, 2009.
Learning Markov Logic Network Structure via Hypergraph Lifting
S. Kok, P. Domingos, International Conference on Machine Learning, 2009.
Unsupervised Methods for Determining Object and Relation Synonyms on the Web
A. Yates, O. Etzioni, Journal of Artificial Intelligence Research, 2009.
2008
Towards the Automated Social Analysis of Situated Speech Data
D. Wyatt, T. Choudhury, J. Bilmes, J. Kitts, International Conference on Ubiquitous Computing, 2008.
A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC
H. Poon, P. Domingos, M. Sumner, AAAI Conference on Artificial Intelligence, 2008.
Hybrid Markov Logic Networks
J. Wang, P. Domingos, AAAI Conference on Artificial Intelligence, 2008.
Information Extraction from Wikipedia: Moving Down the long Tail
F. Wu, R. Hoffmann, D. Weld, Knowledge Discovery and Data Mining, 2008.
Learning Hidden Curved Exponential Random Graph Models to Infer Face-to-Face Interaction Networks from Situated Speech Data
D. Wyatt, T. Choudhury, J. Bilmes, AAAI Conference on Artificial Intelligence, 2008.
Lifted First-Order Belief Propagation
P. Singla, P. Domingos, AAAI Conference on Artificial Intelligence, 2008.
The Tradeoffs Between Open and Traditional Relation Extraction
M. Banko, O. Etzioni, Annual Meeting of the Association for Computational Linguistics, 2008.
Automatically Refining the Wikipedia Infobox Ontology
F. Wu, D. Weld, International World Wide Web Conference, 2008.
Open Information Extraction from the Web
O. Etzioni, S. Soderland, D. Weld, M. Banko, Communications of the ACM, 2008.
It's a Contradiction -- No, It's Not: A Case Study using Functional Relations
A. Ritter, D. Downey, S. Soderland, O. Etzioni, Conference on Empirical Methods in Natural Language Processing, 2008.
Scaling Textual Inference to the Web
S. Schoenmackers, O. Etzioni, D. Weld, Conference on Empirical Methods in Natural Language Processing, 2008.
Discovery of Social Relationships in Consumer Photo Collections using Markov Logic
P. Singla, H. Kautz, J. Luo, A. Gallagher, International Workshop on Semantic Learning and Applications in Multimedia, 2008.
Extracting Semantic Networks from Text via Relational Clustering
S. Kok, P. Domingos, European Conference on Machine Learning, 2008.
Learning Arithmetic Circuits
D. Lowd, P. Domingos, Uncertainty in Artificial Intelligence, 2008.
2007
Lexical Translation with Application to Image Search on the Web
O. Etzioni, K. Reiter, S. Soderland, M. Sammer, Machine Translation Summit, 2007.
Conversation Detection and Speaker Segmentation in Privacy-Sensitive Situated Speech Data
D. Wyatt, T. Choudhury, J. Bilmes, Interspeech, 2007.
Autonomously Semantifying Wikipedia
F. Wu, D. Weld, ACM Conference on Information and Knowledge Management, 2007.
Sparse Information Extraction: Unsupervised Language Models to the Rescue
D. Downey, S. Schoenmackers, O. Etzioni, Annual Meeting of the Association for Computational Linguistics, 2007.
Capturing Spontaneous Conversation and Social Dynamics: A Privacy Sensitive Data Collection Effort
D. Wyatt, T. Choudhury, H. Kautz, International Conference on Acoustic and Speech Signal Processing, 2007.
Unsupervised Resolution of Objects and Relations on the Web
A. Yates, O. Etzioni, Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2007.
Joint Inference in Information Extraction
H. Poon, P. Domingos, AAAI Spring Symposium Series, 2007.
Machine Reading
O. Etzioni, M. Banko, M. Cafarella, AAAI Spring Symposium Series, 2007.
Creating Social Network Models from Sensor Data
D. Wyatt, T. Choudhury, J. Bilmes, Annual Conference on Neural Information Processing Systems, 2007.
Strategies for Lifelong Knowledge Extraction from the Web
M. Banko, O. Etzioni, International Conference on Knowledge Capture, 2007.
A Privacy-Sensitive Approach to Modeling Multi-Person Conversations
D. Wyatt, T. Choudhury, J. Bilmes, H. Kautz, International Joint Conference on Artificial Intelligence, 2007.
Open Information Extraction from the Web
M. Banko, M. Cafarella, S. Soderland, M. Broadhead, O. Etzioni, International Joint Conference on Artificial Intelligence, 2007.
Recursive Random Fields
D. Lowd, P. Domingos, International Joint Conference on Artificial Intelligence, 2007.
Efficient Weight Learning for Markov Logic Networks
D. Lowd, P. Domingos, European Conference on Principles and Practice of Knowledge Discovery in Databases, 2007.
Markov Logic in Infinite Domains
P. Singla, P. Domingos, Uncertainty in Artificial Intelligence, 2007.
Statistical Predicate Invention
S. Kok, P. Domingos, International Conference on Machine Learning, 2007.
Structured Machine Learning: Ten Problems for the Next Ten Years
P. Domingos, International Conference on Inductive Logic Programming, 2007.
2006
Ambiguity Reduction for Machine Translation: Human-Computer Collaboration
M. Sammer, K. Reiter, S. Soderland, K. Kirchhoff, O. Etzioni, biennial conference of the Association for Machine Translation in the Americas, 2006.
Entity Resolution with Markov Logic
P. Singla, P. Domingos, IEEE International Conference on Data Mining, 2006.
Machine Reading
O. Etzioni, M. Banko, M. Cafarella, AAAI Conference on Artificial Intelligence, 2006.
Markov Logic Networks
M. Richardson, P. Domingos, Machine Learning Journal, 2006.
Memory-Efficient Inference in Relational Domains
P. Singla, P. Domingos, AAAI Conference on Artificial Intelligence, 2006.
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies
H. Poon, P. Domingos, AAAI Conference on Artificial Intelligence, 2006.
Unifying Logical and Statistical AI
P. Domingos, S. Kok, H. Poon, M. Richardson, P. Singla, AAAI Conference on Artificial Intelligence, 2006.
2005
A Probabilistic Model of Redundancy in Information Extraction
D. Downey, O. Etzioni, S. Soderland, International Joint Conference on Artificial Intelligence, 2005.
Discriminative Training of Markov Logic Networks
P. Singla, P. Domingos, AAAI Conference on Artificial Intelligence, 2005.
Learning the Structure of Markov Logic Networks
S. Kok, P. Domingos, International Conference on Machine Learning, 2005.
Mining social networks for viral marketing
P. Domingos, IEEE Intelligent Systems, 2005.
Object identification with attribute-mediated dependencies
P. Singla, P. Domingos, European Conference on Principles and Practice of Knowledge Discovery in Databases, 2005.
Naive Bayes Models for Probability Estimation
D. Lowd, P. Domingos, International Conference on Machine Learning, 2005.
2004
iMAP: Discovering Complex Semantic Matches between Database Schemas
R. Dhamankar, Y. Lee, A.H. Doan, A. Halevy, P. Domingos, ACM SIGMOD International Conference on Management of Data, 2004.
Multi-relational record linkage
P. Singla, P. Domingos, KDD Workshop on Multi-Relational Data Mining, 2004.
2003
Trust management for the Semantic Web
M. Richardson, R. Agrawal, P. Domingos, International Semantic Web Conference, 2003.
Building large knowledge bases by mass collaboration
M. Richardson, P. Domingos, International Conference on Knowledge Capture, 2003.
Learning with knowledge from multiple experts
M. Richardson, P. Domingos, International Conference on Machine Learning, 2003.
Mining massive relational databases
G. Hulten, P. Domingos, Y. Abe, International Workshop on Statistical Relational Learning, 2003.
Research on Statistical Relational Learning at the University of Washington
P. Domingos, Y. Abe, C. Anderson, A. Doan, D. Fox, A. Halevy, G. Hulten, H. Kautz, T. Lau, L. Liao, J. Madhavan, D. Mausam, M. Richardson, S. Sanghai, D. Weld, S. Wolfman, Proc. of the IJCAI-2003 Workshop on Learning Statistical Models from Relational Data, 2003.
2002
Learning from Infinite Data in Finite Time
P. Domingos, G. Hulten, Annual Conference on Neural Information Processing Systems, 2002.
Learning to Map between Ontologies on the Semantic Web
A.H. Doan, J. Madhavan, P. Domingos, A. Halevy, International World Wide Web Conference, 2002.
Mining Complex Models from Arbitrarily Large Databases in Constant Time
G. Hulten, P. Domingos, Knowledge Discovery and Data Mining, 2002.
Relational Markov models and their application to adaptive Web navigation
C. Anderson, P. Domingos, D. Weld, Knowledge Discovery and Data Mining, 2002.
2001
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering
P. Domingos, G. Hulten, International Conference on Machine Learning, 2001.
Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach
A.H. Doan, P. Domingos, A. Halevy, ACM SIGMOD International Conference on Management of Data, 2001.
Mining the network value of customers
P. Domingos, M. Richardson, Knowledge Discovery and Data Mining, 2001.
Mining Time-Changing Data Streams
G. Hulten, P. Domingos, L. Spencer, Knowledge Discovery and Data Mining, 2001.
The intelligent surfer: Probabilistic combination of link and content information in PageRank
M. Richardson, P. Domingos, Annual Conference on Neural Information Processing Systems, 2001.
2000
Mining high-speed data streams
G. Hulten, P. Domingos, Knowledge Discovery and Data Mining, 2000.

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