Machine Learning

2017

Zero-Shot Relation Extraction via Reading Comprehension

O. Levy, M. Seo, E. Choi, L. ZettlemoyerConference on Natural Language Learning (CoNLL), 2017.

Commonly Uncommon: Semantic Sparsity in Situation Recognition

M. Yatskar, V. Ordóñez, L. Zettlemoyer, A. FarhadiComputer Vision and Pattern Recognition (CVPR), 2017.
Downloads: DEMO 

Recurrent Additive Networks

K. Lee, O. Levy, L. ZettlemoyerarXiv:1705.07393 , 2017.
Downloads: CODE 

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

M. Joshi, E. Choi, D. Weld, L. ZettlemoyerConference of the Association for Computational Linguistics (ACL), 2017.
Downloads: DATA CODE 

End-to-end Neural Coreference Resolution

K. Lee, L. He, M. Lewis, L. ZettlemoyerConference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
Downloads: CODE DEMO 

Deep Semantic Role Labeling: What Works and What's Next

L. He, K. Lee, M. Lewis, L. ZettlemoyerConference of the Association for Computational Linguistics (ACL), 2017.
Downloads: CODE 

Learning a Neural Semantic Parser from User Feedback

S. Iyer, Y. Konstas, A. Cheung, J. Krishnamurthy, L. ZettlemoyerConference of the Association of Computational Linguistics (ACL), 2017.
Downloads: CODE 

Neural AMR: Sequence-to-Sequence Models for Parsing and Generation

I. Konstas, S. Iyer, M. Yatskar, Y. Choi, L. ZettlemoyerConference of the Association for Computational Linguistics (ACL), 2017.
Downloads: DEMO CODE 

2016

Re-active Learning: Active Learning with Relabeling

C.H. Lin,  Mausam, D.S. WeldAAAI Conference on Artificial Intelligence, 2016.

Learning Prototypical Event Structure from Photo Albums

A. Bosselut, J. Chen, D. Warren, H. Hajishirzi, Y. ChoiConference of the Association for Computational Linguistics (ACL), 2016.
Downloads: WEB DATA 

LSTM CCG Parsing

M. Lewis, K. Lee, L. ZettlemoyerConference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2016.

Situation Recognition: Visual Semantic Role Labeling for Image Understanding

M. Yatskar, L. Zettlemoyer, A. FarhadiProceedings of the Conference of Computer Vision and Pattern Recognition (CVPR), 2016.
Downloads: WEB DATA DEMO 

Summarizing Source Code using a Neural Attention Model

S. Iyer, Y. Konstas, A. Cheung, L. ZettlemoyerAnnual Meeting of the Association for Computational Linguistics (ACL), 2016.
Downloads: CODE 

Human-in-the-Loop Parsing

L. He, J. Michael, M. Lewis, L. ZettlemoyerConference on Empirical Methods in Natural Language Processing (EMNLP), 2016.

A Theme-Rewriting Approach for Generating Algebra Word Problems

R. Koncel-Kedziorski, I. Konstas, L. Zettlemoyer, H. HajishirziConference on Empirical Methods in Natural Language Processing (EMNLP), 2016.

Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects

H. Bagherinezhad, H. Hajishirzi, Y. Choi, A. FarhadiAssociation for the Advancement of Artificial Intelligence (AAAI), 2016.

Global Neural CCG Parsing with Optimality Guarantees

K. Lee, M. Lewis, L. ZettlemoyerConference on Empirical Methods in Natural Language Process (EMNLP), 2016.  *Best Paper Award*

Document-level Sentiment Inference with Social, Faction, and Discourse Context

E. Choi, H. Rashkin, L. Zettlemoyer, Y. ChoiConference of the Association for Computational Linguistics (ACL), 2016.

Globally Coherent Text Generation with Neural Checklist Models

C. Kiddon, L. Zettlemoyer, Y. ChoiConference on Empirical Methods in Natural Language Processing (EMNLP), 2016.

2015

Learning on the Job: Optimal Instruction for Crowdsourcing

J. Bragg,  Mausam, D.S. WeldICML ’15 Workshop on Crowdsourcing and Machine Learning, 2015.

Reactive Learning: Actively Trading Off Larger Noisier Training Sets Against Smaller Cleaner Ones

C.H. Lin,  Mausam, D.S. WeldICML Workshop on Crowdsourcing and Machine Learning and ICML Active Learning Workshop, 2015.

Recursive Decomposition for Nonconvex Optimization

A.L. Friesen, P. DomingosInternational Joint Conference on Artificial Intelligence, 2015.

Design Challenges for Entity Linking

X. Ling, S. Singh, D.S. WeldTransactions of the Association for Computational Linguistics 3, 2015.

Exploiting Parallel News Streams for Unsupervised Event Extraction

C. Zhang, S. Soderland, D.S. WeldTransactions of the Association for Computational Linguistics (TACL) 3, 2015.  

Crawled parallel news streams are available at

http://www.cs.washington.edu/ai/clzhang/sentences.tokens.gz http://www.cs.washington.edu/ai/clzhang/sentences.articleIDs.gz

The github url of this project: https://github.com/zhangcongle/NewsSpikeRe

Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing

H. Izadinia, F. Sadeghi, S.Kumar Divvala, H. Hajishirzi, Y. Choi, A. FarhadiInternational Conference on Computer Vision (ICCV), 2015.  (oral)

Learning to Name Objects

V. Ordonez, W. Liu, J. Deng, Y. Choi, A.C. Berg, T.L. BergCommunications of the ACM (CACM), 2015.  (invited article)

Learning Relational Sum-Product Networks

A. Nath, P. DomingosAAAI Conference on Artificial Intelligence, 2015.

Déjà Image-Captions: A Corpus of Expressive Image Descriptions in Repetition

J. Chen, P. Kuznetsova, D. Warren, Y. ChoiNorth American Chapter of the Association for Computational Linguistics (NAACL), 2015.

Gaussian Processes for Data-Efficient Learning in Robotics and Control

M. Deisenroth, D. Fox, C.E. RasmussenIEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 37:2, 2015.
Downloads: PDF 

2014

Parallel Task Routing for Crowdsourcing

J. Bragg, A. Kolobov,  Mausam, D.S. WeldAAAI Conference on Human Computation and Crowdsourcing, 2014.

Tractable Probabilistic Knowledge Bases: Wikipedia and Beyond

M. Niepert, P. DomingosWorkshop on Statistical Relational AI, 2014.

Tractability through Exchangeability: A New Perspective on Efficient Lifted Inference

M. Niepert, G. Van den BroeckWorkshop on Statistical Relational AI, 2014.

Approximate Lifting Techniques for Belief Propagation

P. Singla, A. Nath, P. DomingosAAAI Conference on Artificial Intelligence, 2014.

Automated Debugging with Tractable Probabilistic Programming

A. Nath, P. DomingosWorkshop on Statistical Relational AI, 2014.

2013

Crowdsourcing Multi-Label Classification for Taxonomy Creation

J. Bragg,  Mausam, D.S. WeldConference on Human Computation & Crowdsourcing (HCOMP)AAAI Press, 2013.   Awarded Best Paper

Joint Coreference Resolution and Named-Entity Linking with Multi-pass Sieves

H. Hajishirzi, L. Zilles, D.S. Weld, L. ZettlemoyerConference on Empirical Methods in Natural Language Processing (EMNLP), 2013.

Harvesting Parallel News Streams to Generate Paraphrases of Event Relations

C. Zhang, D.S. WeldConference on Empirical Methods in Natural Language Processing (EMNLP), 2013.
Downloads: datasets 

Extracting Meronyms for a Biology Knowledge Base using Distant Supervision

X. Ling, P. Clark, D.S. WeldACM Workshop on Automatic Knowledge-Base ConstructionACM, 2013.

POMDP-based control of workflows for crowdsourcing

P. Dai, C. Lin,  Mausam, D.S. WeldArtificial Intelligence 202, 2013.

Learning the Structure of Sum-Product Networks

R. Gens, P. DomingosInternational Conference on Machine LearningOmnipress, 2013.
Downloads: PDF 

Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions

Y. Artzi, L. ZettlemoyerTransactions of the Association for Computational Linguistics 1, 2013.

Tractable Probabilistic Knowledge Bases with Existence Uncertainty

A. Webb, P. DomingosWorkshop on Statistical Relational AI, 2013.

Structured sparse learning of multiple Gaussian graphical model

K. Mohan, M. Chung, S. Han, D. Witten, S.I. Lee, M. FazelAdvances in Neural Information Processing Systems (NIPS), 2013.

Multipath Sparse Coding Using Hierarchical Matching Pursuit

L. Bo, X. Ren, D. FoxIEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
Downloads: PDF BIB 

RGB-D Object Recognition: Features, Algorithms, and a Large Scale Benchmark

K. Lai, L. Bo, X. Ren, D. FoxConsumer Depth Cameras for Computer Vision: Research Topics and Applications, 2013.
Downloads: LINK bibtex 

2012

Unsupervised Feature Learning for RGB-D Based Object Recognition

L. Bo, X. Ren, D. FoxISER, 2012.
Downloads: PDF bibtex 

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. NobleNature Methods 9:5, 2012.

Direct maximization of protein identifications from tandem mass spectra.

M. Spivak, J. Weston, D. Tomazela, M.J. MacCoss, W.S. NobleMolecular & cellular proteomics : MCP 11:2, 2012.

Faster Mass Spectrometry-based Protein Inference: Junction Trees are More Efficient than Sampling and Marginalization by Enumeration.

O. Serang, W.S. NobleIEEE/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. BaileyBioinformatics (Oxford, England) 28:1, 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. NobleNucleic Acids Research In Press, 2012.

Learning Multiple Hierarchical Relational Clusterings

A. Nath, P. DomingosICML-12 Workshop on Statistical Relational Learning, 2012.

Learning STRIPS Operators from Noisy and Incomplete Observations

K. Mourão, L.S. Zettlemoyer, R.P.A. Petrick, M. SteedmanConference on Uncertainty in Artificial Intelligence (UAI) abs/1210.4889, 2012.

ReGroup: Interactive Machine Learning for On-Demand Group Creation in Social Networks

S. Amershi, J. Fogarty, D.S. WeldProceedings of the ACM Conference on Human Factors in Computing Systems (CHI-12), 2012.

How Prior Probability Influences Decision Making: A Unifying Probabilistic Model

Y. Huang, A.L. Friesen, T.D. Hanks, M.N. Shadlen, R.P.N. RaoAdvances in Neural Information Processing Systems (NIPS), 2012.
Downloads: PDF bibtex 

Counting-MLNs: Learning Relational Structure for Decision Making

A. Nath, M. RichardsonAAAI Conference on Artificial Intelligence, 2012.

Discriminative Learning of Sum-Product Networks

R. Gens, P. DomingosNeural Information Processing Systems, 2012.
Downloads: PDF 

A Tractable First-Order Probabilistic Logic

P. Domingos, A. WebbTwenty-Sixth AAAI Conference on Artificial Intelligence, 2012.

A Few Useful Things to Know about Machine Learning

P. DomingosCommunications of the ACM 55:10, 2012.

Detection-based Object Labeling in 3D Scenes

K. Lai, L. Bo, X. Ren, D. FoxICRA, 2012.
Downloads: PDF bibtex video code 

A unified multitask architecture for predicting local protein properties.

Y. Qi, M. Oja, J. Weston, W.S. NoblePloS one 7:3, 2012.

2011

Faster SEQUEST searching for peptide identification from tandem mass spectra.

B.J. Diament, W.S. NobleJournal of proteome research 10:9, 2011.

Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models

C. Kiddon, P. DomingosAAAI Conference on Artificial Intelligence, 2011.

Identifying Relations for Open Information Extraction

A. Fader, S. Soderland, O. EtzioniConference on Empirical Methods in Natural Language Processing, 2011.

Open Information Extraction: the Second Generation

O. Etzioni, A. Fader, J. Christensen, S. Soderland,  MausamInternational 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. WeldProceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2011.
Downloads: Source Code 

Inference Over the Web

S. SchoenmackersPHD Thesis, 2011.

Implementing Weighted Abduction in Markov Logic

J. Blythe, J. Hobbs, P. Domingos, R. Kate, R. MooneyInternational Conference on Computational Semantics, 2011.

Depth Kernel Descriptors for Object Recognition

L. Bo, X. Ren, D. FoxIROS, 2011.
Downloads: PDF BIB Code 

Sparse Distance Learning for Object Recognition Combining RGB and Depth Information

K. Lai, L. Bo, R. X., D. FoxICRA, 2011.  Best Vision Paper Award
Downloads: PDF bibtex slides 

A Scalable Tree-based Approach for Joint Object and Pose Recognition

K. Lai, L. Bo, X. Ren, D. FoxAAAI, 2011.
Downloads: PDF bibtex slides 

Object Recognition with Hierarchical Kernel Descriptors

L. Bo, K. Lai, X. Ren, D. FoxCVPR, 2011.
Downloads: PDF bibtex 

A Large-Scale Hierarchical Multi-View RGB-D Object Dataset

K. Lai, L. Bo, X. Ren, D. FoxICRA, 2011.
Downloads: PDF bibtex poster dataset 

Probabilistic Theorem Proving

V. Gogate, P. DomingosUncertainty in Artificial Intelligence, 2011.

Approximation by Quantization

V. Gogate, P. DomingosUncertainty in Artificial Intelligence, 2011.

Sum-Product Networks: A New Deep Architecture

H. Poon, P. DomingosUncertainty in Artificial Intelligence, 2011.

2010

Learning Efficient Markov Networks

V. Gogate, W. Webb, P. DomingosAnnual Conference on Neural Information Processing Systems, 2010.

Approximate Inference by Compilation to Arithmetic Circuits

D. Lowd, P. DomingosAnnual Conference on Neural Information Processing Systems, 2010.

Lifted Inference Seen from the Other Side: The Tractable Features

A. Jha, V. Gogate, A. Meliou, D. SuciuAnnual Conference on Neural Information Processing Systems, 2010.

Commonsense from the Web: Relation Properties

T. Lin,  Mausam, O. EtzioniAAAI Fall Symposium Series, 2010.

Identifying Functional Relations in Web Text

T. Lin,  Mausam, O. EtzioniConference on Empirical Methods in Natural Language Processing, 2010.

Learning First-Order Horn Clauses from Web Text

S. Schoenmackers, J. Davis, O. Etzioni, D. WeldConference on Empirical Methods in Natural Language Processing, 2010.

Open Information Extraction using Wikipedia

F. Wu, D. WeldAnnual Meeting of the Association for Computational Linguistics, 2010.

Machine Reading: A "Killer App" for Statistical Relational AI

H. Poon, P. DomingosWorkshop on Statistical Relational AI, 2010.

Panlingual Lexical Translation via Probabilistic Inference

Mausam, S. Soderland, O. EtzioniAAAI Conference on Artificial Intelligence, 2010.

Temporal Information Extraction

X. Ling, D. WeldAAAI Conference on Artificial Intelligence, 2010.
Downloads: Data Set 

Efficient Belief Propagation for Utility Maximization and Repeated Inference

A. Nath, P. DomingosAAAI Conference on Artificial Intelligence, 2010.

Efficient Lifting for Online Probabilistic Inference

A. Nath, P. DomingosAAAI Conference on Artificial Intelligence, 2010.
Downloads: Dataset 

Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models

D. Wyatt, T. Choudhury, J. BilmesAAAI Conference on Artificial Intelligence, 2010.

A Latent Dirichlet Allocation method for Selectional Preferences

A. Ritter,  Mausam, O. EtzioniAnnual Meeting of the Association for Computational Linguistics, 2010.

Leveraging Ontologies for Lifted Probabilistic Inference and Learning

C. Kiddon, P. DomingosWorkshop on Statistical Relational AI, 2010.

Exploiting Logical Structure in Lifted Probabilistic Inference

V. Gogate, P. DomingosWorkshop on Statistical Relational AI, 2010.

Approximate Lifted Belief Propagation

P. Singla, A. Nath, P. DomingosWorkshop on Statistical Relational AI, 2010.

Learning 5000 Relational Extractors

R. Hoffmann, D. WeldAnnual Meeting of the Association for Computational Linguistics, 2010.

Formula-Based Probabilistic Inference

V. Gogate, P. DomingosUncertainty in Artificial Intelligence, 2010.

Extracting Sequences from the Web

A. Fader, S. Soderland, O. EtzioniAnnual Meeting of the Association for Computational Linguistics, 2010.

Bottom-Up Learning of Markov Network Structure

J. Davis, P. DomingosInternational 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. SchoenmackersAnnual Conference of the North American Chapter of the Association for Computational Linguistics, 2010.

Learning Markov Logic Networks Using Structural Motifs

S. Kok, P. DomingosInternational Conference on Machine Learning, 2010.

Semantic Role Labeling for Open Information Extraction

Mausam, S. Soderland, O. Etzioni, J. ChristensenAnnual Conference of the North American Chapter of the Association for Computational Linguistics, 2010.

Kernel Descriptors for Visual Recognition

L. Bo, X. Ren, D. FoxNIPS, 2010.
Downloads: PDF BIB Code 

Twin Gaussian Processes for Structured Prediction

L. Bo, C. SminchisescuInternational Journal of Computer Vision, 2010.

Analysis of a Probabilistic Model of Redundancy in Unsupervised Information Extraction

O. Etzioni, S. Soderland, D. DowneyArtificial Intelligence 174:11, 2010.

2009

Efficient Match Kernels between Sets of Features for Visual Recognition

L. Bo, C. SminchisescuAnnual Conference on Neural Information Processing Systems, 2009.

Dynamic Multi-Valued Network Models for Predicting Face-to-Face Conversations

D. Wyatt, J. Bilmes, T. ChoudhuryAnnual Conference on Neural Information Processing Systems, 2009.

Conditional Neural Fields

J. Peng, L. Bo, J. XuAnnual Conference on Neural Information Processing Systems, 2009.

Identifying Interesting Assertions from the Web

T. Lin, O. Etzioni, J. FogartyACM Conference on Information and Knowledge Management, 2009.

Unsupervised Semantic Parsing

H. Poon, P. DomingosConference on Empirical Methods in Natural Language Processing, 2009.

A Rose is a Roos is a Ruusu: Querying Translations for Web Image Search

J. Christensen,  Mausam, O. EtzioniAnnual 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. BilmesAnnual Meeting of the Association for Computational Linguistics, 2009.

Lemmatic Machine Translation

S. Soderland,  Mausam, O. Etzioni, C. Lim, J. Pool, B. QinMachine Translation Summit, 2009.

A Language for Relational Decision Theory

A. Nath, P. DomingosInternational Workshop on Statistical Relational Learning, 2009.

Deep Transfer via Second-Order Markov Logic

J. Davis, P. DomingosInternational 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. WeldConference on Human Factors in Computing Systems, 2009.

Amplifying Community Content Creation with Mixed Initiative Information Extraction

R. Hoffmann, S. Amershi, K. Patel, F. Wu, J. Fogarty, D. WeldConference on Human Factors in Computing Systems, 2009.

What Is This, Anyway: Automatic Hypernym Discovery

A. Ritter, S. Soderland, O. EtzioniAAAI Spring Symposium Series, 2009.

Collective Modeling of Human Social Behavior

D. WyattAAAI Spring Symposium Series, 2009.

Unsupervised Methods for Determining Object and Relation Synonyms on the Web

A. Yates, O. EtzioniJournal of Artificial Intelligence Research, 2009.

Learning Markov Logic Network Structure via Hypergraph Lifting

S. Kok, P. DomingosInternational Conference on Machine Learning, 2009.

2008

Open Information Extraction from the Web

O. Etzioni, S. Soderland, D. Weld, M. BankoCommunications 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. EtzioniConference on Empirical Methods in Natural Language Processing, 2008.

Scaling Textual Inference to the Web

S. Schoenmackers, O. Etzioni, D. WeldConference on Empirical Methods in Natural Language Processing, 2008.

Towards the Automated Social Analysis of Situated Speech Data

D. Wyatt, T. Choudhury, J. Bilmes, J. KittsInternational Conference on Ubiquitous Computing, 2008.

Lifted First-Order Belief Propagation

P. Singla, P. DomingosAAAI Conference on Artificial Intelligence, 2008.

Hybrid Markov Logic Networks

J. Wang, P. DomingosAAAI Conference on Artificial Intelligence, 2008.

A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC

H. Poon, P. Domingos, M. SumnerAAAI Conference on Artificial Intelligence, 2008.

Information Extraction from Wikipedia: Moving Down the long Tail

F. Wu, R. Hoffmann, D. WeldKnowledge 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. BilmesAAAI Conference on Artificial Intelligence, 2008.

The Tradeoffs Between Open and Traditional Relation Extraction

M. Banko, O. EtzioniAnnual Meeting of the Association for Computational Linguistics, 2008.

Automatically Refining the Wikipedia Infobox Ontology

F. Wu, D. WeldInternational World Wide Web Conference, 2008.

Extracting Semantic Networks from Text via Relational Clustering

S. Kok, P. DomingosEuropean Conference on Machine Learning, 2008.

Learning Arithmetic Circuits

D. Lowd, P. DomingosUncertainty in Artificial Intelligence, 2008.

Discovery of Social Relationships in Consumer Photo Collections using Markov Logic

P. Singla, H. Kautz, J. Luo, A. GallagherInternational Workshop on Semantic Learning and Applications in Multimedia, 2008.

2007

Creating Social Network Models from Sensor Data

D. Wyatt, T. Choudhury, J. BilmesAnnual Conference on Neural Information Processing Systems, 2007.

Strategies for Lifelong Knowledge Extraction from the Web

M. Banko, O. EtzioniInternational Conference on Knowledge Capture, 2007.

Lexical Translation with Application to Image Search on the Web

O. Etzioni, K. Reiter, S. Soderland, M. SammerMachine Translation Summit, 2007.

Conversation Detection and Speaker Segmentation in Privacy-Sensitive Situated Speech Data

D. Wyatt, T. Choudhury, J. BilmesInterspeech, 2007.

Autonomously Semantifying Wikipedia

F. Wu, D. WeldACM Conference on Information and Knowledge Management, 2007.

Sparse Information Extraction: Unsupervised Language Models to the Rescue

D. Downey, S. Schoenmackers, O. EtzioniAnnual 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. KautzInternational Conference on Acoustic and Speech Signal Processing, 2007.

Unsupervised Resolution of Objects and Relations on the Web

A. Yates, O. EtzioniAnnual Conference of the North American Chapter of the Association for Computational Linguistics, 2007.

Joint Inference in Information Extraction

H. Poon, P. DomingosAAAI Spring Symposium Series, 2007.

Machine Reading

O. Etzioni, M. Banko, M. CafarellaAAAI Spring Symposium Series, 2007.

Recursive Random Fields

D. Lowd, P. DomingosInternational Joint Conference on Artificial Intelligence, 2007.

A Privacy-Sensitive Approach to Modeling Multi-Person Conversations

D. Wyatt, T. Choudhury, J. Bilmes, H. KautzInternational Joint Conference on Artificial Intelligence, 2007.

Open Information Extraction from the Web

M. Banko, M. Cafarella, S. Soderland, M. Broadhead, O. EtzioniInternational Joint Conference on Artificial Intelligence, 2007.

Structured Machine Learning: Ten Problems for the Next Ten Years

P. DomingosInternational Conference on Inductive Logic Programming, 2007.

Statistical Predicate Invention

S. Kok, P. DomingosInternational Conference on Machine Learning, 2007.

Efficient Weight Learning for Markov Logic Networks

D. Lowd, P. DomingosEuropean Conference on Principles and Practice of Knowledge Discovery in Databases, 2007.

Markov Logic in Infinite Domains

P. Singla, P. DomingosUncertainty in Artificial Intelligence, 2007.

2006

Ambiguity Reduction for Machine Translation: Human-Computer Collaboration

M. Sammer, K. Reiter, S. Soderland, K. Kirchhoff, O. Etzionibiennial conference of the Association for Machine Translation in the Americas, 2006.

Memory-Efficient Inference in Relational Domains

P. Singla, P. DomingosAAAI Conference on Artificial Intelligence, 2006.

Unifying Logical and Statistical AI

P. Domingos, S. Kok, H. Poon, M. Richardson, P. SinglaAAAI Conference on Artificial Intelligence, 2006.

Sound and Efficient Inference with Probabilistic and Deterministic Dependencies

H. Poon, P. DomingosAAAI Conference on Artificial Intelligence, 2006.

Entity Resolution with Markov Logic

P. Singla, P. DomingosIEEE International Conference on Data Mining, 2006.

Machine Reading

O. Etzioni, M. Banko, M. CafarellaAAAI Conference on Artificial Intelligence, 2006.

Markov Logic Networks

M. Richardson, P. DomingosMachine Learning Journal, 2006.

2005

A Probabilistic Model of Redundancy in Information Extraction

D. Downey, O. Etzioni, S. SoderlandInternational Joint Conference on Artificial Intelligence, 2005.

Discriminative Training of Markov Logic Networks

P. Singla, P. DomingosAAAI Conference on Artificial Intelligence, 2005.

Naive Bayes Models for Probability Estimation

D. Lowd, P. DomingosInternational Conference on Machine Learning, 2005.

Object identification with attribute-mediated dependencies

P. Singla, P. DomingosEuropean Conference on Principles and Practice of Knowledge Discovery in Databases, 2005.

Mining social networks for viral marketing

P. DomingosIEEE Intelligent Systems, 2005.

Learning the Structure of Markov Logic Networks

S. Kok, P. DomingosInternational Conference on Machine Learning, 2005.

2004

iMAP: Discovering Complex Semantic Matches between Database Schemas

R. Dhamankar, Y. Lee, A.H. Doan, A. Halevy, P. DomingosACM SIGMOD International Conference on Management of Data, 2004.

Multi-relational record linkage

P. Singla, P. DomingosKDD Workshop on Multi-Relational Data Mining, 2004.

2003

Trust management for the Semantic Web

M. Richardson, R. Agrawal, P. DomingosInternational Semantic Web Conference, 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. WolfmanProc. of the IJCAI-2003 Workshop on Learning Statistical Models from Relational Data, 2003.

Mining massive relational databases

G. Hulten, P. Domingos, Y. AbeInternational Workshop on Statistical Relational Learning, 2003.

Building large knowledge bases by mass collaboration

M. Richardson, P. DomingosInternational Conference on Knowledge Capture, 2003.

Learning with knowledge from multiple experts

M. Richardson, P. DomingosInternational Conference on Machine Learning, 2003.

2002

Learning from Infinite Data in Finite Time

P. Domingos, G. HultenAnnual Conference on Neural Information Processing Systems, 2002.

Relational Markov models and their application to adaptive Web navigation

C. Anderson, P. Domingos, D. WeldKnowledge Discovery and Data Mining, 2002.

Learning to Map between Ontologies on the Semantic Web

A.H. Doan, J. Madhavan, P. Domingos, A. HalevyInternational World Wide Web Conference, 2002.

Mining Complex Models from Arbitrarily Large Databases in Constant Time

G. Hulten, P. DomingosKnowledge Discovery and Data Mining, 2002.

2001

Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach

A.H. Doan, P. Domingos, A. HalevyACM SIGMOD International Conference on Management of Data, 2001.

A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering

P. Domingos, G. HultenInternational Conference on Machine Learning, 2001.

The intelligent surfer: Probabilistic combination of link and content information in PageRank

M. Richardson, P. DomingosAnnual Conference on Neural Information Processing Systems, 2001.

Mining Time-Changing Data Streams

G. Hulten, P. Domingos, L. SpencerKnowledge Discovery and Data Mining, 2001.

Mining the network value of customers

P. Domingos, M. RichardsonKnowledge Discovery and Data Mining, 2001.

2000

Mining high-speed data streams

G. Hulten, P. DomingosKnowledge Discovery and Data Mining, 2000.