Journal Articles
Research 
Specific Topics
| Constrained Conditional Models | Learning Based Programming | Psycholinguistics | |||
| Machine Learning for NLP | Trustworthiness of Information | Machine Learning/Learning Theory | |||
| Natural Learning Semantics | Spelling, Text Correction & ESL | Knowledge Representation & Inference | |||
| ILP Formations for NLP | Un/Semi-Supervised Learning & Adaption | Machine Learning for Computer Vision |
Years
2012 2011 2009 2008 2007 2006 2005
2004 2002 2001 1999 1998 1997 1996
All Years
2004 2002 2001 1999 1998 1997 1996
All Years
2012
- Exploring the Wikipedia Structure in Local and Global Classification of Taxonomic Relations
Q. Do and D. Roth
Journal of Natural Language Engineering (JNLE) - 2012
2011
- Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks
O. J. Mengshoel and D. Roth and D. C. Wilkins
Journal of Automated Reasoning - 2011 - Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks
O. J. Mengshoel and D. C. Wilkins and D. Roth
IEEE Transactions on Knowledge and Data Engineering - 2011
2009
- Learning Multi-Linear Representations
D. Roth and R. Samdani
Machine Learning - 2009 - Guest Editors Introduction: Recognizing Textual Entailment: Rational, Evaluation and Approaches
I. Dagan and B. Dolan and B. Magnini and D. Roth
Journal of Natural Language Engineering - 2009
2008
- The Importance of Syntactic Parsing and Inference in Semantic Role Labeling
V. Punyakanok and D. Roth and W. Yih
Computational Linguistics - 2008 - Learning Hebrew Roots: Machine Learning with Linguistic Constraints
E. Daya and D. Roth and S. Wintner
Computational Linguistics - 2008 - A Survey of First-Order Probabilistic Models
R. de Salvo Braz and E. Amir and D. Roth
Innovations in Bayesian Networks - 2008
2007
- Global Inference for Entity and Relation Identification via a Linear Programming Formulation
D. Roth and W. Yih
Introduction to Statistical Relational Learning - 2007 - Lifted First-Order Probabilistic Inference
R. de Salvo Braz and E. Amir and D. Roth
Introduction to Statistical Relational Learning - 2007 - Audio-Visual Affect Recognition
Z. Zeng and J. Tu and M. Liu and T. Huang and B. Pianfetti and D. Roth and S. Levinson
IEEE Transactions on Multimedia - 2007
2006
- An Inference Model for Semantic Entailment in Natural Language
R. de Salvo Braz and R. Girju and V. Punyakanok and D. Roth and M. Sammons
Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop, Revised Selected Papers - 2006 - Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
O. J. Mengshoel and D. Roth and D. C. Wilkins
Artificial Intelligence - 2006
2005
- Generalization Bounds for the Area Under the ROC Curve
S. Agarwal and T. Graepel and R. Herbrich and S. Har-Peled and D. Roth
Journal of Machine Learning Research - 2005 - Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
R. Khardon and D. Roth and R. Servedio
Journal of Machine Learning Research - 2005 - Guest Editors Introduction: Machine Learning in Speech and Language Technologies
P. Fung and D. Roth
Machine Learning - 2005 - Learning based Programming
D. Roth
Innovations in Machine Learning: Theory and Applications - 2005 - Semantic Integration in Text: From Ambiguous Names to Identifiable Entities
X. Li and P. Morie and D. Roth
AI Magazine. Special Issue on Semantic Integration - 2005 - Learning Question Classifiers: The Role of Semantic Information
X. Li and D. Roth
Journal of Natural Language Engineering - 2005
2004
- Learning to Detect Objects in Images via a Sparse, Part-Based Representation
S. Agarwal and A. Awan and D. Roth
IEEE Transactions on Pattern Analysis and Machine Intelligence - 2004 - Mapping Dependencies Trees: An Application to Question Answering
V. Punyakanok and D. Roth and W. Yih
Proc. of the International Symposium on Artificial Intelligence and Mathematics (AIM) - 2004
2002
- Learning to Recognize 3D Objects
D. Roth and M. Yang and N. Ahuja
Neural Computation - 2002 - Learning Cost-Sensitive Active Classifiers
R. Greiner and A. Grove and D. Roth
Artificial Intelligence - 2002
2001
- Gene Recognition based on DAG shortest paths
J. Chuang and D. Roth
Bioinformatics - 2001 - Linear concepts and hidden variables
A. Grove and D. Roth
Machine Learning - 2001
1999
- Learning to Reason with a Restricted View
R. Khardon and D. Roth
Machine Learning - 1999 - Reasoning with Examples: Propositional Formulae and Database Dependencies
R. Khardon and H. Mannila and D. Roth
Acta Informatica - 1999 - A Winnow based approach to Context-Sensitive Spelling Correction
A. R. Golding and D. Roth
Machine Learning - 1999 - Linearizable Read/Write Objects
M. Mavronicolas and D. Roth
Theoretical Computer Science - 1999
1998
- Learning and Reasoning with Connectionist Representations
D. Roth
Neural Computing Surveys - 1998 - On learning read-k satisfy-j DNF
H. Aizenstein and A. Blum and R. Khardon and A. Kushilevitz and L. Pitt and D. Roth
SIAM Journal of Computing - 1998
1997
- Defaults and Relevance in Model Based Reasoning
R. Khardon and D. Roth
Artificial Intelligence - 1997 - Learning to Reason
R. Khardon and D. Roth
Journal of the ACM - 1997 - Finding the Maximum Area Axis-Parallel Rectangle in a Polygon
K. Daniels and V. J. Milenkovic and D. Roth
Computational Geometry: Theory and Applications - 1997
1996
- On the hardness of approximate reasoning
D. Roth
Artificial Intelligence - 1996 - On Learning Visual Concepts and DNF Formulae
A. Kushilevitz and D. Roth
Machine Learning - 1996 - Reasoning with Models
R. Khardon and D. Roth
Artificial Intelligence - 1996
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