Dan Roth

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2013
176Using domain knowledge and domain-inspired discourse model for coreference resolution for clinical narratives. Prateek Jindal, Dan Roth. JAMIA (20): 356-362 (2013). Web SearchBibTeXDownload
2012
175Automatic Event Extraction with Structured Preference Modeling. Wei Lu, Dan Roth. ACL (1) 2012, 835-844. Web SearchBibTeXDownload
174BiasTrust: teaching biased users about controversial topics. V. G. Vinod Vydiswaran, ChengXiang Zhai, Dan Roth, Peter Pirolli. CIKM 2012, 1905-1909. Web SearchBibTeXDownload
173Unsupervised discovery of opposing opinion networks from forum discussions. Yue Lu, Hongning Wang, ChengXiang Zhai, Dan Roth. CIKM 2012, 1642-1646. Web SearchBibTeXDownload
172Using Knowledge and Constraints To Find the Best Antecedent. Prateek Jindal, Dan Roth. COLING 2012, 1327-1342. Web SearchBibTeXDownload
171Efficient Decomposed Learning for Structured Prediction. Rajhans Samdani, Dan Roth. CoRR (abs/1206.4630) (2012). Web SearchBibTeXDownload
170Joint Inference for Event Timeline Construction. Quang Do, Wei Lu, Dan Roth. EMNLP-CoNLL 2012, 677-687. Web SearchBibTeXDownload
169Learning-based Multi-Sieve Co-reference Resolution with Knowledge. Lev-Arie Ratinov, Dan Roth. EMNLP-CoNLL 2012, 1234-1244. Web SearchBibTeXDownload
168On Amortizing Inference Cost for Structured Prediction. Vivek Srikumar, Gourab Kundu, Dan Roth. EMNLP-CoNLL 2012, 1114-1124. Web SearchBibTeXDownload
167A Discriminative Model for Query Spelling Correction with Latent Structural SVM. Huizhong Duan, Yanen Li, ChengXiang Zhai, Dan Roth. EMNLP-CoNLL 2012, 1511-1521. Web SearchBibTeXDownload
166Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP. Dan Goldwasser, Vivek Srikumar, Dan Roth. HLT-NAACL 2012. Web SearchBibTeXDownload
165Unified Expectation Maximization. Rajhans Samdani, Ming-Wei Chang, Dan Roth. HLT-NAACL 2012, 688-698. Web SearchBibTeXDownload
164A Robust Shallow Temporal Reasoning System. Ran Zhao, Quang Do, Dan Roth. HLT-NAACL 2012, 29-32. Web SearchBibTeXDownload
163Efficient Pattern-Based Time Series Classification on GPU. Kai-Wei Chang, Biplab Deka, Wen-mei W. Hwu, Dan Roth. ICDM 2012, 131-140. Web SearchBibTeXDownload
162An NLP Curator (or: How I Learned to Stop Worrying and Love NLP Pipelines). James Clarke, Vivek Srikumar, Mark Sammons, Dan Roth. LREC 2012, 3276-3283. Web SearchBibTeXDownload
161Structured learning with constrained conditional models. Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth. Machine Learning (88): 399-431 (2012). Web SearchBibTeXDownload
160Exploiting the Wikipedia structure in local and global classification of taxonomic relations. Quang Xuan Do, Dan Roth. Natural Language Engineering (18): 235-262 (2012). Web SearchBibTeXDownload
2011
159Confidence Driven Unsupervised Semantic Parsing. Dan Goldwasser, Roi Reichart, James Clarke, Dan Roth. ACL 2011, 1486-1495. Web SearchBibTeXDownload
158Local and Global Algorithms for Disambiguation to Wikipedia. Lev-Arie Ratinov, Dan Roth, Doug Downey, Mike Anderson. ACL 2011, 1375-1384. Web SearchBibTeXDownload
157Exploiting Syntactico-Semantic Structures for Relation Extraction. Yee Seng Chan, Dan Roth. ACL 2011, 551-560. Web SearchBibTeXDownload
156Algorithm Selection and Model Adaptation for ESL Correction Tasks. Alla Rozovskaya, Dan Roth. ACL 2011, 924-933. Web SearchBibTeXDownload
155Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms. Roni Khardon, Dan Roth, Rocco A. Servedio. CoRR (abs/1109.2141) (2011). Web SearchBibTeXDownload
154A Joint Model for Extended Semantic Role Labeling. Vivek Srikumar, Dan Roth. EMNLP 2011, 129-139. Web SearchBibTeXDownload
153Minimally Supervised Event Causality Identification. Quang Do, Yee Seng Chan, Dan Roth. EMNLP 2011, 294-303. Web SearchBibTeXDownload
152Learning from Negative Examples in Set-Expansion. Prateek Jindal, Dan Roth. ICDM 2011, 1110-1115. Web SearchBibTeXDownload
151Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks. Ole J. Mengshoel, David C. Wilkins, Dan Roth. IEEE Trans. Knowl. Data Eng. (23): 235-247 (2011). Web SearchBibTeXDownload
150Making Better Informed Trust Decisions with Generalized Fact-Finding. Jeff Pasternack, Dan Roth. IJCAI 2011, 2324-2329. Web SearchBibTeXDownload
149Learning from Natural Instructions. Dan Goldwasser, Dan Roth. IJCAI 2011, 1794-1800. Web SearchBibTeXDownload
148Online Latent Structure Training for Language Acquisition. Michael Connor, Cynthia Fisher, Dan Roth. IJCAI 2011, 1782-1787. Web SearchBibTeXDownload
147Apollo: Towards factfinding in participatory sensing. Hieu 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. Web SearchBibTeXDownload
146Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks. Ole J. Mengshoel, Dan Roth, David C. Wilkins. J. Autom. Reasoning (46): 103-160 (2011). Web SearchBibTeXDownload
145Selective block minimization for faster convergence of limited memory large-scale linear models. Kai-Wei Chang, Dan Roth. KDD 2011, 699-707. Web SearchBibTeXDownload
144Content-driven trust propagation framework. V. G. Vinod Vydiswaran, ChengXiang Zhai, Dan Roth. KDD 2011, 974-982. Web SearchBibTeXDownload
143Generalized fact-finding. Jeff Pasternack, Dan Roth. WWW (Companion Volume) 2011, 99-100. Web SearchBibTeXDownload
2010
142"Ask Not What Textual Entailment Can Do for You...". Mark Sammons, V. G. Vinod Vydiswaran, Dan Roth. ACL 2010, 1199-1208. Web SearchBibTeXDownload
141Starting from Scratch in Semantic Role Labeling. Michael Connor, Yael Gertner, Cynthia Fisher, Dan Roth. ACL 2010, 989-998. Web SearchBibTeXDownload
140Exploiting Background Knowledge for Relation Extraction. Yee Seng Chan, Dan Roth. COLING 2010, 152-160. Web SearchBibTeXDownload
139Knowing What to Believe (when you already know something). Jeff Pasternack, Dan Roth. COLING 2010, 877-885. Web SearchBibTeXDownload
138Citation Author Topic Model in Expert Search. Yuancheng Tu, Nikhil Johri, Dan Roth, Julia Hockenmaier. COLING (Posters) 2010, 1265-1273. Web SearchBibTeXDownload
137Automatic Model Adaptation for Complex Structured Domains. Geoffrey Levine, Gerald DeJong, Li-Lun Wang, Rajhans Samdani, Shankar Vembu, Dan Roth. ECML/PKDD (2) 2010, 243-258. Web SearchBibTeXDownload
136Constraints Based Taxonomic Relation Classification. Quang Do, Dan Roth. EMNLP 2010, 1099-1109. Web SearchBibTeXDownload
135The Necessity of Combining Adaptation Methods. Ming-Wei Chang, Michael Connor, Dan Roth. EMNLP 2010, 767-777. Web SearchBibTeXDownload
134Generating Confusion Sets for Context-Sensitive Error Correction. Alla Rozovskaya, Dan Roth. EMNLP 2010, 961-970. Web SearchBibTeXDownload
133Training Paradigms for Correcting Errors in Grammar and Usage. Alla Rozovskaya, Dan Roth. HLT-NAACL 2010, 154-162. Web SearchBibTeXDownload
132Discriminative Learning over Constrained Latent Representations. Ming-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Srikumar. HLT-NAACL 2010, 429-437. Web SearchBibTeXDownload
131Structured Output Learning with Indirect Supervision. Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Dan Roth. ICML 2010, 199-206. Web SearchBibTeXDownload
130Unsupervised Aggregation for Classification Problems with Large Numbers of Categories. Ivan Titov, Alexandre Klementiev, Kevin Small, Dan Roth. Journal of Machine Learning Research - Proceedings Track (9): 836-843 (2010). Web SearchBibTeXDownload
129Learning Based Java for Rapid Development of NLP Systems. Nick Rizzolo, Dan Roth. LREC 2010. Web SearchBibTeXDownload
128Recognizing textual entailment: Rational, evaluation and approaches - Erratum. Ido Dagan, Bill Dolan, Bernardo Magnini, Dan Roth. Natural Language Engineering (16): 105 (2010). Web SearchBibTeXDownload
127Making Sense of Unstructured Textual Data. Dan Roth. Web Intelligence and Security - Advances in Data and Text Mining Techniques for Detecting and Preventing Terrorist Activities on the Web 2010, 195-206. Web SearchBibTeXDownload
2009
126A Framework for Entailed Relation Recognition. Dan Roth, Mark Sammons, V. G. Vinod Vydiswaran. ACL/IJCNLP (Short Papers) 2009, 57-60. Web SearchBibTeXDownload
125Learning better transliterations. Jeff Pasternack, Dan Roth. CIKM 2009, 177-186. Web SearchBibTeXDownload
124Learning Multi-linear Representations of Distributions for Efficient Inference. Dan Roth, Rajhans Samdani. ECML/PKDD (1) 2009, 11. Web SearchBibTeXDownload
123Reading to Learn: Constructing Features from Semantic Abstracts. Jacob Eisenstein, James Clarke, Dan Goldwasser, Dan Roth. EMNLP 2009, 958-967. Web SearchBibTeXDownload
122Unsupervised Constraint Driven Learning For Transliteration Discovery. Ming-Wei Chang, Dan Goldwasser, Dan Roth, Yuancheng Tu. HLT-NAACL 2009, 299-307. Web SearchBibTeXDownload
121Aspect Guided Text Categorization with Unobserved Labels. Dan Roth, Yuancheng Tu. ICDM 2009, 962-967. Web SearchBibTeXDownload
120Unsupervised Rank Aggregation with Domain-Specific Expertise. Alexandre Klementiev, Dan Roth, Kevin Small, Ivan Titov. IJCAI 2009, 1101-1106. Web SearchBibTeXDownload
119Sequential Learning of Classifiers for Structured Prediction Problems. Dan Roth, Kevin Small, Ivan Titov. Journal of Machine Learning Research - Proceedings Track (5): 440-447 (2009). Web SearchBibTeXDownload
118Learning multi-linear representations of distributions for efficient inference. Dan Roth, Rajhans Samdani. Machine Learning (76): 195-209 (2009). Web SearchBibTeXDownload
117Extracting article text from the web with maximum subsequence segmentation. Jeff Pasternack, Dan Roth. WWW 2009, 971-980. Web SearchBibTeXDownload
2008
116Proactive Intrusion Detection. Benjamin Liebald, Dan Roth, Neelay Shah, Vivek Srikumar. AAAI 2008, 772-777. Web SearchBibTeXDownload
115Importance of Semantic Representation: Dataless Classification. Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth, Vivek Srikumar. AAAI 2008, 830-835. Web SearchBibTeXDownload
114Active Learning for Pipeline Models. Dan Roth, Kevin Small. AAAI 2008, 683-688. Web SearchBibTeXDownload
113Learning and Inference with Constraints. Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo, Dan Roth. AAAI 2008, 1513-1518. Web SearchBibTeXDownload
112Extraction of Entailed Semantic Relations Through Syntax-Based Comma Resolution. Vivek Srikumar, Roi Reichart, Mark Sammons, Ari Rappoport, Dan Roth. ACL 2008, 1030-1038. Web SearchBibTeXDownload
111Active Sample Selection for Named Entity Transliteration. Dan Goldwasser, Dan Roth. ACL (Short Papers) 2008, 53-56. Web SearchBibTeXDownload
110The Importance of Syntactic Parsing and Inference in Semantic Role Labeling. Vasin Punyakanok, Dan Roth, Wen-tau Yih. Computational Linguistics (34): 257-287 (2008). Web SearchBibTeXDownload
109Identifying Semitic Roots: Machine Learning with Linguistic Constraints. Ezra Daya, Dan Roth, Shuly Wintner. Computational Linguistics (34): 429-448 (2008). Web SearchBibTeXDownload
108Transliteration as Constrained Optimization. Dan Goldwasser, Dan Roth. EMNLP 2008, 353-362. Web SearchBibTeXDownload
107Understanding the Value of Features for Coreference Resolution. Eric Bengtson, Dan Roth. EMNLP 2008, 294-303. Web SearchBibTeXDownload
106Unsupervised rank aggregation with distance-based models. Alexandre Klementiev, Dan Roth, Kevin Small. ICML 2008, 472-479. Web SearchBibTeXDownload
105A Survey of First-Order Probabilistic Models. Rodrigo de Salvo Braz, Eyal Amir, Dan Roth. Innovations in Bayesian Networks 2008, 289-317. Web SearchBibTeXDownload
104Which "Apple" are you talking about ?. Mandar Rahurkar, Dan Roth, Thomas S. Huang. WWW 2008, 1197-1198. Web SearchBibTeXDownload
2007
103Guiding Semi-Supervision with Constraint-Driven Learning. Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth. ACL 2007. Web SearchBibTeXDownload
102Context Sensitive Paraphrasing with a Global Unsupervised Classifier. Michael Connor, Dan Roth. ECML 2007, 104-115. Web SearchBibTeXDownload
101An Unsupervised Learning Algorithm for Rank Aggregation. Alexandre Klementiev, Dan Roth, Kevin Small. ECML 2007, 616-623. Web SearchBibTeXDownload
100Modeling Discriminative Global Inference. Nicholas Rizzolo, Dan Roth. ICSC 2007, 597-604. Web SearchBibTeXDownload
99Audio-Visual Affect Recognition. Zhihong Zeng, Jilin Tu, Ming Liu, Thomas S. Huang, Brian Pianfetti, Dan Roth, Stephen E. Levinson. IEEE Transactions on Multimedia (9): 424-428 (2007). Web SearchBibTeXDownload
98Maximum Margin Coresets for Active and Noise Tolerant Learning. Sariel Har-Peled, Dan Roth, Dav Zimak. IJCAI 2007, 836-841. Web SearchBibTeXDownload
2006
97MPE and Partial Inversion in Lifted Probabilistic Variable Elimination. Rodrigo de Salvo Braz, Eyal Amir, Dan Roth. AAAI 2006, 1123-1130. Web SearchBibTeXDownload
96A Pipeline Framework for Dependency Parsing. Ming-Wei Chang, Quang Do, Dan Roth. ACL 2006. Web SearchBibTeXDownload
95Weakly Supervised Named Entity Transliteration and Discovery from Multilingual Comparable Corpora. Alexandre Klementiev, Dan Roth. ACL 2006. Web SearchBibTeXDownload
94Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering. Ole J. Mengshoel, David C. Wilkins, Dan Roth. Artif. Intell. (170): 1137-1174 (2006). Web SearchBibTeXDownload
93Margin-Based Active Learning for Structured Output Spaces. Dan Roth, Kevin Small. ECML 2006, 413-424. Web SearchBibTeXDownload
92Named Entity Transliteration and Discovery from Multilingual Comparable Corpora. Alexandre Klementiev, Dan Roth. HLT-NAACL 2006. Web SearchBibTeXDownload
91Learning question classifiers: the role of semantic information. Xin Li, Dan Roth. Natural Language Engineering (12): 229-249 (2006). Web SearchBibTeXDownload
2005
90Semantic Integration in Text: From Ambiguous Names to Identifiable Entities. Xin Li, Paul Morie, Dan Roth. AI Magazine (26): 45-58 (2005). Web SearchBibTeXDownload
89Learnability of Bipartite Ranking Functions. Shivani Agarwal, Dan Roth. COLT 2005, 16-31. Web SearchBibTeXDownload
88Emotions from Text: Machine Learning for Text-based Emotion Prediction. Cecilia Ovesdotter Alm, Dan Roth, Richard Sproat. HLT/EMNLP 2005. Web SearchBibTeXDownload
87Demonstrating an Interactive Semantic Role Labeling System. Vasin Punyakanok, Dan Roth, Mark Sammons, Wen-tau Yih. HLT/EMNLP 2005. Web SearchBibTeXDownload
86Automated and Adaptive Threshold Setting: Enabling Technology for Autonomy and Self-Management. Brian Ziebart, Dan Roth, Roy H. Campbell, Anind K. Dey. ICAC 2005, 204-215. Web SearchBibTeXDownload
85Integer linear programming inference for conditional random fields. Dan Roth, Wen-tau Yih. ICML 2005, 736-743. Web SearchBibTeXDownload
84The Necessity of Syntactic Parsing for Semantic Role Labeling. Vasin Punyakanok, Dan Roth, Wen-tau Yih. IJCAI 2005, 1117-1123. Web SearchBibTeXDownload
83Learning and Inference over Constrained Output. Vasin Punyakanok, Dan Roth, Wen-tau Yih, Dav Zimak. IJCAI 2005, 1124-1129. Web SearchBibTeXDownload
82Lifted First-Order Probabilistic Inference. Rodrigo de Salvo Braz, Eyal Amir, Dan Roth. IJCAI 2005, 1319-1325. Web SearchBibTeXDownload
81Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms. Roni Khardon, Dan Roth, Rocco A. Servedio. J. Artif. Intell. Res. (JAIR) (24): 341-356 (2005). Web SearchBibTeXDownload
80Generalization Bounds for the Area Under the ROC Curve. Shivani Agarwal, Thore Graepel, Ralf Herbrich, Sariel Har-Peled, Dan Roth. Journal of Machine Learning Research (6): 393-425 (2005). Web SearchBibTeXDownload
79Guest Editors Introduction: Machine Learning in Speech and Language Technologies. Pascale Fung, Dan Roth. Machine Learning (60): 5-9 (2005). Web SearchBibTeXDownload
78An Inference Model for Semantic Entailment in Natural Language. Rodrigo de Salvo Braz, Roxana Girju, Vasin Punyakanok, Dan Roth, Mark Sammons. MLCW 2005, 261-286. Web SearchBibTeXDownload
2004
77Identification and Tracing of Ambiguous Names: Discriminative and Generative Approaches. Xin Li, Paul Morie, Dan Roth. AAAI 2004, 419-424. Web SearchBibTeXDownload
76Semantic Role Labeling Via Integer Linear Programming Inference. Vasin Punyakanok, Dan Roth, Wen-tau Yih, Dav Zimak. COLING 2004. Web SearchBibTeXDownload
75Learning Hebrew Roots: Machine Learning with Linguistic Constraints. Ezra Daya, Dan Roth, Shuly Wintner. EMNLP 2004, 357-364. Web SearchBibTeXDownload
74Robust Reading: Identification and Tracing of Ambiguous Names. Xin Li, Paul Morie, Dan Roth. HLT-NAACL 2004, 17-24. Web SearchBibTeXDownload
73Bimodal HCI-related affect recognition. Zhihong Zeng, Jilin Tu, Ming Liu, Tong Zhang, Nicholas Rizzolo, ZhenQiu Zhang, Thomas S. Huang, Dan Roth, Stephen E. Levinson. ICMI 2004, 137-143. Web SearchBibTeXDownload
72Learning to Detect Objects in Images via a Sparse, Part-Based Representation. Shivani Agarwal, Aatif Awan, Dan Roth. IEEE Trans. Pattern Anal. Mach. Intell. (26): 1475-1490 (2004). Web SearchBibTeXDownload
71A Large Deviation Bound for the Area Under the ROC Curve. Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan Roth. NIPS 2004. Web SearchBibTeXDownload
2003
70Margin Distribution and Learning. Ashutosh Garg, Dan Roth. ICML 2003, 210-217. Web SearchBibTeXDownload
69On Kernel Methods for Relational Learning. Chad M. Cumby, Dan Roth. ICML 2003, 107-114. Web SearchBibTeXDownload
2002
68Constraint Classification: A New Approach to Multiclass Classification. Sariel Har-Peled, Dan Roth, Dav Zimak. ALT 2002, 365-379. Web SearchBibTeXDownload
67Learning cost-sensitive active classifiers. Russell Greiner, Adam J. Grove, Dan Roth. Artif. Intell. (139): 137-174 (2002). Web SearchBibTeXDownload
66Learning Question Classifiers. Xin Li, Dan Roth. COLING 2002. Web SearchBibTeXDownload
65Probabilistic Reasoning for Entity & Relation Recognition. Dan Roth, Wen-tau Yih. COLING 2002. Web SearchBibTeXDownload
64Learning a Sparse Representation for Object Detection. Shivani Agarwal, Dan Roth. ECCV (4) 2002, 113-130. Web SearchBibTeXDownload
63A Tale of Two Classifiers: SNoW vs. SVM in Visual Recognition. Ming-Hsuan Yang, Dan Roth, Narendra Ahuja. ECCV (4) 2002, 685-699. Web SearchBibTeXDownload
62Learning and Inference for Clause Identification. Xavier Carreras, Lluís Màrquez, Vasin Punyakanok, Dan Roth. ECML 2002, 35-47. Web SearchBibTeXDownload
61On generalization bounds, projection profile, and margin distribution. Ashutosh Garg, Sariel Har-Peled, Dan Roth. ICML 2002, 171-178. Web SearchBibTeX
60Learning with Feature Description Logics. Chad M. Cumby, Dan Roth. ILP 2002, 32-47. Web SearchBibTeXDownload
59Learning to Recognize Three-Dimensional Objects. Dan Roth, Ming-Hsuan Yang, Narendra Ahuja. Neural Computation (14): 1071-1103 (2002). Web SearchBibTeXDownload
58Constraint Classification for Multiclass Classification and Ranking. Sariel Har-Peled, Dan Roth, Dav Zimak. NIPS 2002, 785-792. Web SearchBibTeXDownload
57Reasoning with Classifiers. Dan Roth. PKDD 2002, 489-493. Web SearchBibTeXDownload
56Question-Answering via Enhanced Understanding of Questions. Dan Roth, Chad M. Cumby, Xin Li, Paul Morie, Ramya Nagarajan, Nick Rizzolo, Kevin Small, Wen-tau Yih. TREC 2002. Web SearchBibTeXDownload
2001
55Learning Coherent Concepts. Ashutosh Garg, Dan Roth. ALT 2001, 135-150. Web SearchBibTeXDownload
54The Use of Classifiers in Sequential Inference. Vasin Punyakanok, Dan Roth. CoRR (cs.LG/0111003) (2001). Web SearchBibTeXDownload
53A Sequential Model for Multi-Class Classification. Yair Even-Zohar, Dan Roth. CoRR (cs.AI/0106044) (2001). Web SearchBibTeXDownload
52Understanding Probabilistic Classifiers. Ashutosh Garg, Dan Roth. ECML 2001, 179-191. Web SearchBibTeXDownload
51Scaling Up Context-Sensitive Text Correction. Andrew J. Carlson, Jeffrey Rosen, Dan Roth. IAAI 2001, 45-50. Web SearchBibTeX
50Face detection using large margin classifiers. Ming-Hsuan Yang, Dan Roth, Narendra Ahuja. ICIP (2) 2001, 665-668. Web SearchBibTeXDownload
49Relational Learning via Propositional Algorithms: An Information Extraction Case Study. Dan Roth, Wen-tau Yih. IJCAI 2001, 1257-1263. Web SearchBibTeX
48Gene recognition based on DAG shortest paths. John S. Chuang, Dan Roth. ISMB (Supplement of Bioinformatics) 2001, 56-64. Web SearchBibTeX
47Linear Concepts and Hidden Variables. Adam J. Grove, Dan Roth. Machine Learning (42): 123-141 (2001). Web SearchBibTeXDownload
46Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms. Roni Khardon, Dan Roth, Rocco A. Servedio. NIPS 2001, 423-430. Web SearchBibTeXDownload
45Learning Components for A Question-Answering System. Dan Roth, Gio Kao Kao, Xin Li, Ramya Nagarajan, Vasin Punyakanok, Nick Rizzolo, Wen-tau Yih, Cecilia Ovesdotter Alm, Liam Gerard Moran. TREC 2001. Web SearchBibTeXDownload
2000
44Toward a Theory of Learning Coherent Concepts. Dan Roth, Dmitry Zelenko. AAAI/IAAI 2000, 639-644. Web SearchBibTeXDownload
43A Classification Approach to Word Prediction. Yair Even-Zohar, Dan Roth. ANLP 2000, 124-131. Web SearchBibTeXDownload
42Applying System Combination to Base Noun Phrase Identification. Erik F. Tjong Kim Sang, Walter Daelemans, Hervé Déjean, Rob Koeling, Yuval Krymolowski, Vasin Punyakanok, Dan Roth. COLING (cs.CL/0008012): 857-863 (2000). Web SearchBibTeXDownload
41A Learning Approach to Shallow Parsing. Marcia Muñoz, Vasin Punyakanok, Dan Roth, Dav Zimak. CoRR (cs.LG/0008022) (2000). Web SearchBibTeXDownload
40Learning to Recognize Objects. Dan Roth, Ming-Hsuan Yang, Narendra Ahuja. CVPR 2000, 1724-1731. Web SearchBibTeXDownload
39Learning to Recognize 3D Objects with SNoW. Ming-Hsuan Yang, Dan Roth, Narendra Ahuja. ECCV (1) 2000, 439-454. Web SearchBibTeXDownload
38Relational Representations that Facilitate Learning. Chad M. Cumby, Dan Roth. KR 2000, 425-434. Web SearchBibTeX
37The Use of Classifiers in Sequential Inference. Vasin Punyakanok, Dan Roth. NIPS 2000, 995-1001. Web SearchBibTeX
1999
36Reasoning with Examples: Propositional Formulae and Database Dependencies. Roni Khardon, Heikki Mannila, Dan Roth. Acta Inf. (36): 267-286 (1999). Cited by 21Web SearchBibTeXDownload
35Learning in Natural Language. Dan Roth. IJCAI 1999, 898-904. Web SearchBibTeX
34Relational Learning for NLP using Linear Threshold Elements. Roni Khardon, Dan Roth, Leslie G. Valiant. IJCAI 1999, 911-919. Web SearchBibTeX
33A Winnow-Based Approach to Context-Sensitive Spelling Correction. Andrew R. Golding, Dan Roth. Machine Learning (34): 107-130 (1999). Web SearchBibTeXDownload
32Learning to Reason with a Restricted View. Roni Khardon, Dan Roth. Machine Learning (35): 95-116 (1999). Web SearchBibTeXDownload
31A SNoW-Based Face Detector. Ming-Hsuan Yang, Dan Roth, Narendra Ahuja. NIPS 1999, 862-868. Web SearchBibTeXDownload
30Coherent Concepts, Robust Learning. Dan Roth, Dmitry Zelenko. SOFSEM 1999, 264-276. Web SearchBibTeXDownload
29Linearizable Read/Write Objects. Marios Mavronicolas, Dan Roth. Theor. Comput. Sci. (220): 267-319 (1999). Web SearchBibTeXDownload
1998
28Learning to Resolve Natural Language Ambiguities: A Unified Approach. Dan Roth. AAAI/IAAI (cs.CL/9811010): 806-813 (1998). Web SearchBibTeXDownload
27Part of Speech Tagging Using a Network of Linear Separators. Dan Roth, Dmitry Zelenko. COLING-ACL 1998, 1136-1142. Web SearchBibTeXDownload
26A Winnow-Based Approach to Context-Sensitive Spelling Correction. Andrew R. Golding, Dan Roth. CoRR (cs.LG/9811003) (1998). Web SearchBibTeXDownload
25Clustering Appearances of 3D Objects. Ronen Basri, Dan Roth, David W. Jacobs. CVPR 1998, 414-420. Web SearchBibTeXDownload
24On Learning Read-k-Satisfy-j DNF. Avrim Blum, Roni Khardon, Eyal Kushilevitz, Leonard Pitt, Dan Roth, Dan Roth. SIAM J. Comput. (27): 1515-1530 (1998). Web SearchBibTeXDownload
1997
23Defaults and Relevance in Model-Based Reasoning. Roni Khardon, Dan Roth. Artif. Intell. (97): 169-193 (1997). Web SearchBibTeXDownload
22Finding the Largest Area Axis-parallel Rectangle in a Polygon. Karen L. Daniels, Victor J. Milenkovic, Dan Roth. Comput. Geom. (7): 125-148 (1997). Cited by 22Web SearchBibTeXDownload
21Mistake-Driven Learning in Text Categorization. Ido Dagan, Yael Karov, Dan Roth. CoRR (cmp-lg/9706006) (1997). Web SearchBibTeXDownload
20Learning to reason. Roni Khardon, Dan Roth. J. ACM (44): 697-725 (1997). Web SearchBibTeXDownload
19Learning to Perform Knowledge-Intensive Inferences. Dan Roth. MFCS 1997, 108-109. Web SearchBibTeXDownload
18Linear Concepts and Hidden Variables: An Empirical Study. Adam J. Grove, Dan Roth. NIPS 1997. Web SearchBibTeX
1996
17A Connectionist Framework for Reasoning: Reasoning with Examples. Dan Roth. AAAI/IAAI, Vol. 2 1996, 1256-1261. Web SearchBibTeXDownload
16On the Hardness of Approximate Reasoning. Dan Roth. Artif. Intell. (82): 273-302 (1996). Web SearchBibTeXDownload
15Reasoning with Models. Roni Khardon, Dan Roth. Artif. Intell. (87): 187-213 (1996). Web SearchBibTeXDownload
14Applying Winnow to Context-Sensitive Spelling Correction. Andrew R. Golding, Dan Roth. ICML (cmp-lg/9607024): 182-190 (1996). Web SearchBibTeXDownload
13Learning Active Classifiers. Russell Greiner, Adam J. Grove, Dan Roth. ICML 1996, 207-215. Web SearchBibTeX
12On Learning Visual Concepts and DNF Formulae. Eyal Kushilevitz, Dan Roth. Machine Learning (24): 65-85 (1996). Web SearchBibTeXDownload
11Learning in Order to Reason: The Approach. Dan Roth. SOFSEM 1996, 113-124. Web SearchBibTeXDownload
1995
10Learning to Reason with a Restricted View. Roni Khardon, Dan Roth. COLT 1995, 301-310. Web SearchBibTeXDownload
9Learning to Reason: The Non-Monotonic Case. Dan Roth. IJCAI 1995, 1178-1184. Web SearchBibTeX
8Default-Reasoning with Models. Roni Khardon, Dan Roth. IJCAI 1995, 319-327. Web SearchBibTeX
1994
7Reasoning with Models. Roni Khardon, Dan Roth. AAAI 1994, 1148-1153. Web SearchBibTeXDownload
6Learning to Reason. Roni Khardon, Dan Roth. AAAI 1994, 682-687. Web SearchBibTeXDownload
5On Learning Read-k-Satisfy-j DNF. Avrim Blum, Roni Khardon, Eyal Kushilevitz, Leonard Pitt, Dan Roth, Dan Roth. COLT 1994, 110-117. Web SearchBibTeXDownload
1993
4Finding the Maximum Area Axis-parallel Rectangle in a Polygon. Karen L. Daniels, Victor Milenkovic, Dan Roth. CCCG 1993, 322-327. Cited by 7Web SearchBibTeX
3On Learning Visual Concepts and DNF Formulae. Eyal Kushilevitz, Dan Roth. COLT 1993, 317-326. Web SearchBibTeXDownload
2On the Hardness of Approximate Reasoning. Dan Roth. IJCAI 1993, 613-619. Web SearchBibTeX
1992
1Efficient, Strongly Consistent Implementations of Shared Memory (Extended Abstract). Marios Mavronicolas, Dan Roth. WDAG 1992, 346-361. Web SearchBibTeXDownload
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References
1. ^ AAAI-08 – IAAI-08 Organizing and Program Committees - Retrieved 2012-01-12 - details
2. ^ AAAI-06 Conference Officials and Committee - Retrieved 2012-01-12 - details
3. ^ http://www.cse.unsw.edu.au/~icml2002/refs.html - Retrieved 2012-01-12 - details
4. ^ <FallColloq.2010.html> - Retrieved 2012-01-12 - details
5. ^ Department Talks | Department of Computer Science | University of Pittsburgh - Retrieved 2013-05-23 - details
6. ^ Forum for Artificial Intelligence - Retrieved 2012-01-12 - details
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