Dan Roth - researchr alias

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2011

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2011, San Francisco, California, USA, August 7-11, 2011Wolfram Burgard, Dan Roth, editors, AAAI Press, 2011.

Exploiting Syntactico-Semantic Structures for Relation ExtractionYee Seng Chan, Dan Roth. acl 2011: 551-560 [doi]

Selective block minimization for faster convergence of limited memory large-scale linear modelsKai-Wei Chang, Dan Roth. kdd 2011: 699-707 [doi]

Online Latent Structure Training for Language AcquisitionMichael Connor, Cynthia Fisher, Dan Roth. IJCAI 2011: 1782-1787 [doi]

Learning from Natural InstructionsDan Goldwasser, Dan Roth. IJCAI 2011: 1794-1800 [doi]

Confidence Driven Unsupervised Semantic ParsingDan Goldwasser, Roi Reichart, James Clarke, Dan Roth. acl 2011: 1486-1495 [doi]

Apollo: Towards factfinding in participatory sensingH. Khac Le, Jeff Pasternack, Hossein Ahmadi, M. Gupta, Y. Sun, Tarek F. Abdelzaher, J. Han, Dan Roth, Boleslaw K. Szymanski, Sibel Adali. ipsn 2011: 129-130 [doi]

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian NetworksOle J. Mengshoel, Dan Roth, David C. Wilkins. JAR, 46(2):103-160, 2011. [doi]

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian NetworksOle J. Mengshoel, David C. Wilkins, Dan Roth. tkde, 23(2):235-247, 2011. [doi]

Generalized fact-findingJeff Pasternack, Dan Roth. WWW 2011: 99-100 [doi]

Making Better Informed Trust Decisions with Generalized Fact-FindingJeff Pasternack, Dan Roth. IJCAI 2011: 2324-2329 [doi]

Local and Global Algorithms for Disambiguation to WikipediaLev-Arie Ratinov, Dan Roth, Doug Downey, Mike Anderson. acl 2011: 1375-1384 [doi]

Algorithm Selection and Model Adaptation for ESL Correction TasksAlla Rozovskaya, Dan Roth. acl 2011: 924-933 [doi]

Content-driven trust propagation frameworkV. G. Vinod Vydiswaran, ChengXiang Zhai, Dan Roth. kdd 2011: 974-982 [doi]

2010

Exploiting Background Knowledge for Relation ExtractionYee Seng Chan, Dan Roth. COLING 2010: 152-160 [doi]

Structured Output Learning with Indirect SupervisionMing-Wei Chang, Vivek Srikumar, Dan Goldwasser, Dan Roth. icml 2010: 199-206 [doi]

Discriminative Learning over Constrained Latent RepresentationsMing-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Srikumar. naacl 2009: 429-437 [doi]

The Necessity of Combining Adaptation MethodsMing-Wei Chang, Michael Connor, Dan Roth. emnlp 2010: 767-777 [doi]

Starting from Scratch in Semantic Role LabelingMichael Connor, Yael Gertner, Cynthia Fisher, Dan Roth. acl 2010: 989-998 [doi]

Recognizing textual entailment: Rational, evaluation and approaches - ErratumIdo Dagan, Bill Dolan, Bernardo Magnini, Dan Roth. nle, 16(1):105, 2010. [doi]

Constraints Based Taxonomic Relation ClassificationQuang Do, Dan Roth. emnlp 2010: 1099-1109 [doi]

Automatic Model Adaptation for Complex Structured DomainsGeoffrey Levine, Gerald DeJong, Li-Lun Wang, Rajhans Samdani, Shankar Vembu, Dan Roth. pkdd 2010: 243-258 [doi]

Knowing What to Believe (when you already know something)Jeff Pasternack, Dan Roth. COLING 2010: 877-885 [doi]

Learning Based Java for Rapid Development of NLP SystemsNick Rizzolo, Dan Roth. lrec 2010: [doi]

Generating Confusion Sets for Context-Sensitive Error CorrectionAlla Rozovskaya, Dan Roth. emnlp 2010: 961-970 [doi]

Training Paradigms for Correcting Errors in Grammar and UsageAlla Rozovskaya, Dan Roth. naacl 2009: 154-162 [doi]

Ask Not What Textual Entailment Can Do for You... Mark Sammons, V. G. Vinod Vydiswaran, Dan Roth. acl 2010: 1199-1208 [doi]

Unsupervised Aggregation for Classification Problems with Large Numbers of CategoriesIvan Titov, Alexandre Klementiev, Kevin Small, Dan Roth. jmlr, 9:836-843, 2010. [doi]

Citation Author Topic Model in Expert SearchYuancheng Tu, Nikhil Johri, Dan Roth, Julia Hockenmaier. COLING 2010: 1265-1273 [doi]

2009

Unsupervised Constraint Driven Learning For Transliteration DiscoveryMing-Wei Chang, Dan Goldwasser, Dan Roth, Yuancheng Tu. naacl 2009: 299-307 [doi]

Reading to Learn: Constructing Features from Semantic AbstractsJacob Eisenstein, James Clarke, Dan Goldwasser, Dan Roth. emnlp 2009: 958-967 [doi]

Unsupervised Rank Aggregation with Domain-Specific ExpertiseAlexandre Klementiev, Dan Roth, Kevin Small, Ivan Titov. IJCAI 2009: 1101-1106 [doi]

Extracting article text from the web with maximum subsequence segmentationJeff Pasternack, Dan Roth. WWW 2009: 971-980 [doi]

Learning better transliterationsJeff Pasternack, Dan Roth. CIKM 2009: 177-186 [doi]

Learning Multi-linear Representations of Distributions for Efficient InferenceDan Roth, Rajhans Samdani. pkdd 2009: 11 [doi]

Aspect Guided Text Categorization with Unobserved LabelsDan Roth, Yuancheng Tu. icdm 2009: 962-967 [doi]

Learning multi-linear representations of distributions for efficient inferenceDan Roth, Rajhans Samdani. ml, 76(2-3):195-209, 2009. [doi]

A Framework for Entailed Relation RecognitionDan Roth, Mark Sammons, V. G. Vinod Vydiswaran. acl 2009: 57-60 [doi]

Sequential Learning of Classifiers for Structured Prediction ProblemsDan Roth, Kevin Small, Ivan Titov. jmlr, 5:440-447, 2009. [doi]

2008

Understanding the Value of Features for Coreference ResolutionEric Bengtson, Dan Roth. emnlp 2008: 294-303 [doi]

Importance of Semantic Representation: Dataless ClassificationMing-Wei Chang, Lev-Arie Ratinov, Dan Roth, Vivek Srikumar. AAAI 2008: 830-835

Learning and Inference with ConstraintsMing-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo, Dan Roth. AAAI 2008: 1513-1518

Identifying Semitic Roots: Machine Learning with Linguistic ConstraintsEzra Daya, Dan Roth, Shuly Wintner. coling, 34(3):429-448, 2008. [doi]

A Survey of First-Order Probabilistic ModelsRodrigo de Salvo Braz, Eyal Amir, Dan Roth. In Dawn E. Holmes, Lakhmi C. Jain, editors, Innovations in Bayesian Networks: Theory and Applications. Volume 156 of Studies in Computational Intelligence, pages 289-317, Springer, 2008. [doi]

Active Sample Selection for Named Entity TransliterationDan Goldwasser, Dan Roth. acl 2008: 53-56 [doi]

Transliteration as Constrained OptimizationDan Goldwasser, Dan Roth. emnlp 2008: 353-362 [doi]

Unsupervised rank aggregation with distance-based modelsAlexandre Klementiev, Dan Roth, Kevin Small. icml 2008: 472-479 [doi]

Proactive Intrusion DetectionBenjamin Liebald, Dan Roth, Neelay Shah, Vivek Srikumar. AAAI 2008: 772-777

The Importance of Syntactic Parsing and Inference in Semantic Role LabelingVasin Punyakanok, Dan Roth, Wen-tau Yih. coling, 34(2):257-287, 2008. [doi]

Which Apple are you talking about ?Mandar Rahurkar, Dan Roth, Thomas S. Huang. WWW 2008: 1197-1198 [doi]

Active Learning for Pipeline ModelsDan Roth, Kevin Small. AAAI 2008: 683-688

Extraction of Entailed Semantic Relations Through Syntax-Based Comma ResolutionVivek Srikumar, Roi Reichart, Mark Sammons, Ari Rappoport, Dan Roth. acl 2008: 1030-1038 [doi]

2007

2006

2005

Generalization Bounds for the Area Under the ROC CurveShivani Agarwal, Thore Graepel, Ralf Herbrich, Sariel Har-Peled, Dan Roth. jmlr, 6:393-425, 2005. [doi]

Learnability of Bipartite Ranking FunctionsShivani Agarwal, Dan Roth. colt 2005: 16-31 [doi]

Emotions from Text: Machine Learning for Text-based Emotion PredictionCecilia Ovesdotter Alm, Dan Roth, Richard Sproat. naacl 2005: [doi]

Lifted First-Order Probabilistic InferenceRodrigo de Salvo Braz, Eyal Amir, Dan Roth. IJCAI 2005: 1319-1325 [doi]

An Inference Model for Semantic Entailment in Natural LanguageRodrigo de Salvo Braz, Roxana Girju, Vasin Punyakanok, Dan Roth, Mark Sammons. mlcw 2006: 261-286 [doi]

An Inference Model for Semantic Entailment in Natural LanguageRodrigo de Salvo Braz, Roxana Girju, Vasin Punyakanok, Dan Roth, Mark Sammons. IJCAI 2005: 1678-1679 [doi]

An Inference Model for Semantic Entailment in Natural LanguageRodrigo de Salvo Braz, Roxana Girju, Vasin Punyakanok, Dan Roth, Mark Sammons. AAAI 2005: 1043-1049

Guest Editors Introduction: Machine Learning in Speech and Language TechnologiesPascale Fung, Dan Roth. ml, 60(1-3):5-9, 2005. [doi]

Efficiency versus Convergence of Boolean Kernels for On-Line Learning AlgorithmsRoni Khardon, Dan Roth, Rocco A. Servedio. jair, 24:341-356, 2005. [doi]

Semantic Integration in Text: From Ambiguous Names to Identifiable EntitiesXin Li, Paul Morie, Dan Roth. aim, 26(1):45-58, 2005.

Demonstrating an Interactive Semantic Role Labeling SystemVasin Punyakanok, Dan Roth, Mark Sammons, Wen-tau Yih. naacl 2005: [doi]

Learning and Inference over Constrained OutputVasin Punyakanok, Dan Roth, Wen-tau Yih, Dav Zimak. IJCAI 2005: 1124-1129 [doi]

The Necessity of Syntactic Parsing for Semantic Role LabelingVasin Punyakanok, Dan Roth, Wen-tau Yih. IJCAI 2005: 1117-1123 [doi]

Integer linear programming inference for conditional random fieldsDan Roth, Wen-tau Yih. icml 2005: 736-743 [doi]

Automated and Adaptive Threshold Setting: Enabling Technology for Autonomy and Self-ManagementBrian Ziebart, Dan Roth, Roy H. Campbell, Anind K. Dey. icac 2005: 204-215 [doi]

2004

A Large Deviation Bound for the Area Under the ROC CurveShivani Agarwal, Thore Graepel, Ralf Herbrich, Dan Roth. nips 2004: [doi]

Learning to Detect Objects in Images via a Sparse, Part-Based RepresentationShivani Agarwal, Aatif Awan, Dan Roth. pami, 26(11):1475-1490, 2004. [doi]

Learning Hebrew Roots: Machine Learning with Linguistic ConstraintsEzra Daya, Dan Roth, Shuly Wintner. emnlp 2004: 357-364 [doi]

Robust Reading: Identification and Tracing of Ambiguous NamesXin Li, Paul Morie, Dan Roth. naacl 2004: 17-24 [doi]

Identification and Tracing of Ambiguous Names: Discriminative and Generative ApproachesXin Li, Paul Morie, Dan Roth. AAAI 2004: 419-424

Bimodal HCI-related affect recognitionZhihong Zeng, Jilin Tu, Ming Liu, Tong Zhang, Nicholas Rizzolo, ZhenQiu Zhang, Thomas S. Huang, Dan Roth, Stephen E. Levinson. icmi 2004: 137-143 [doi]

2003

On Kernel Methods for Relational LearningChad M. Cumby, Dan Roth. icml 2003: 107-114

Margin Distribution and LearningAshutosh Garg, Dan Roth. icml 2003: 210-217

2002

Learning a Sparse Representation for Object DetectionShivani Agarwal, Dan Roth. eccv 2002: 113-130 [doi]

Learning and Inference for Clause IdentificationXavier Carreras, Lluís Màrquez, Vasin Punyakanok, Dan Roth. ecml 2002: 35-47 [doi]

Learning with Feature Description LogicsChad M. Cumby, Dan Roth. ilp 2003: 32-47 [doi]

On generalization bounds, projection profile, and margin distributionAshutosh Garg, Sariel Har-Peled, Dan Roth. icml 2002: 171-178

Learning cost-sensitive active classifiersRussell Greiner, Adam J. Grove, Dan Roth. ai, 139(2):137-174, 2002. [doi]

Constraint Classification for Multiclass Classification and RankingSariel Har-Peled, Dan Roth, Dav Zimak. nips 2003: 785-792 [doi]

Learning Question ClassifiersXin Li, Dan Roth. COLING 2002: [doi]

Probabilistic Reasoning for Entity & Relation RecognitionDan Roth, Wen-tau Yih. COLING 2002: [doi]

Reasoning with ClassifiersDan Roth. ecml 2002: 506-510 [doi]

Reasoning with ClassifiersDan Roth. pkdd 2002: 489-493 [doi]

Question-Answering via Enhanced Understanding of QuestionsDan Roth, Chad M. Cumby, Xin Li, Paul Morie, Ramya Nagarajan, Nick Rizzolo, Kevin Small, Wen-tau Yih. trec 2002: [doi]

Learning to Recognize Three-Dimensional ObjectsDan Roth, Ming-Hsuan Yang, Narendra Ahuja. neco, 14(5):1071-1103, 2002. [doi]

A Tale of Two Classifiers: SNoW vs. SVM in Visual RecognitionMing-Hsuan Yang, Dan Roth, Narendra Ahuja. eccv 2002: 685-699 [doi]

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