Journal papers

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Multi-Class Confidence Weighted Algorithms Koby Crammer, Mark Dredze and Alex Kulesza Empirical Methods in Natural Language Processing (EMNLP), 2009	pdf
New Regularized Algorithms for Transductive Learning Partha Pratim Talukdar and Koby Crammer European Conference on Machine Learning (ECML-PKDD), 2009	pdf
How to Loose Confidence: Probabilistic Linear Machines for Multiclass Classification Hui Lin, Jeff Bilmes and Koby Crammer Conference of the International Speech Communication Association (Interspeech), 2009	pdf
Gaussian Margin Machines Koby Crammer, Mehryar Mohri and Fernando Pereira Proceedings of the Twelfth Intentional Conference on Artificial Intelligence and Statistics (AISTATS), 2009	pdf
Exact Convex Confidence-Weighted Learning Koby Crammer, Mark Dredze and Fernando Pereira Proceedings of the Twenty Second Annual Conference on Neural Information Processing Systems (NIPS), 2008	pdf
Online Methods for Multi-Domain Learning and Adaptation Mark Dredze and Koby Crammer Conference on Empirical Methods in Natural Language Processing (EMNLP), 2008	pdf
One-Class Clustering in the Text Domain Ron Bekkerman and Koby Crammer Conference on Empirical Methods in Natural Language Processing (EMNLP), 2008	pdf
Learning to Create Data-Integrating Queries Partha Pratim Talukdar, Marie Jacob, Mohammad Salman Mehmood, Koby Crammer, Zack Ives, Fernando Pereira and Sudipto Guha Proceedings of the 34th International Conference on Very Large Databases (VLDB 2008)	pdf ps gz
DRASO: Declaratively Regularized Alternating Structural Optimization Partha Pratim Talukdar, John Blitzer, Ted Sandler, Mark Dredze, Koby Crammer and Fernando Pereira ICML 2008 Workshop on Prior Knowledge for Text and Language Processing	pdf ps gz
Active Learning with Confidence Mark Dredze and Koby Crammer Proceeding of the Association for Computational Linguistics (ACL), 2008	pdf ps gz
Confidence-Weighted Linear Classification Mark Dredze, Koby Crammer and Fernando Pereira Proceedings of the 25th International Conference on Machine Learning (ICML), 2008	pdf ps gz
A Rate-Distortion One-Class Model and its Applications to Clustering Koby Crammer, Partha Pratim Talukdar and Fernando Pereira Proceedings of the 25th International Conference on Machine Learning (ICML), 2008	pdf ps gz
Learning Bounds for Domain Adaptation John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira and Jennifer Wortman Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems (NIPS), 2007. Spotlight slide and short audio (Stay with the beat )	pdf
A Conservative Aggressive Subspace Tracker Koby Crammer Proceedings of the 10th European Conference on Speech Comunication and Technology (Interspeech), 2007	pdf ps gz
Automatic Code Assignment to Medical Text Koby Crammer, Mark Dredze, Kuzman Ganchev, Partha Pratim Talukdar and Steven Carroll BioNLP 2007	pdf
Penn/UMass/CHOP BiocreativeII Systems Kuzman Ganchev, Koby Crammer, Fernando Pereira, Gideon Mann, Kedar Bellare, Andrew McCallum, Steven Carroll, Yang Jin, and Peter White Proceedings of the Biocreative II Workshop, 2007	pdf
Learning from Multiple Sources Koby Crammer, Michael Kearns, and Jennifer Wortman Proceedings of the Nineteenth Annual Conference on Neural Information Processing Systems (NIPS), 2006.	pdf ps gz
Analysis of Representations for Domain Adaptation Shai Ben-David, John Blitzer, Koby Crammer, and Fernando Pereira Proceedings of the Nineteenth Annual Conference on Neural Information Processing Systems (NIPS), 2006.	pdf
Robust Support Vector Machine Training via Convex Outlier Ablation Linli Xu, Koby Crammer, Dale Schuurmans Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), 2006.	pdf
Discriminative Learning vis Semidefinite Probabilities Koby Crammer and Amir Globerson Proceedings of Uncertainty in Artificial Intelligence (UAI), 2006	pdf
Online Tracking of Linear Subspaces Koby Crammer Proceedings of the Nineteenth Annual Conference on Computational Learning Theory (COLT) , 2006.	pdf
Room Impulse Response Estimation Using Sparse Online Prediction and Absolute Loss Koby Crammer and Daniel D. Lee The 31st International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2006.	pdf
Learning from Data of Variable Quality Koby Crammer, Michael Kearns, Jennifer Wortman Proceedings of the Eighteenth Annual Conference on Neural Information Processing Systems (NIPS), 2005.	ps gz pdf
Flexible Text Segmentation with Structured Multilabel Classification Ryan McDonald, Koby Crammer and Fernando Pereira Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, 2005.	ps gz pdf
Online Large-Margin Training of Dependency Parsers Ryan McDonald, Koby Crammer and Fernando Pereira 43rd Annual Meeting of the Association for Computational Linguistics, 2005. Detailed technical report	ps gz pdf
Loss Bounds for Online Category Ranking Koby Crammer and Yoram Singer Proceedings of the Eighteenth Annual Conference on Computational Learning Theory (COLT) , 2005.	ps gz pdf
A Temporal Kernel-Based Model for Tracking Hand-Movements from Neural Activities Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia and Yoram Singer Proceedings of the Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), 2004.	ps gz pdf
A Needle in a Haystack: Local One-Class Optimization Koby Crammer and Gal Chechik Proceedings of the Twenty-First International Conference on Machine Learning (ICML), 2004.	ps gz pdf
Online Passive-Aggressive Algorithms Koby Crammer, Ofer Dekel, Shai Shalev-Shwartz and Yoram Singer Proceedings of the Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), 2003.	ps gz pdf
Online Classification on a Budget Koby Crammer, Jaz Kandola and Yoram Singer Proceedings of the Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), 2003.	ps gz pdf
Learning Algorithms for Enclosing Points in Bregmanian Spheres Koby Crammer and Yoram Singer Proceedings of the Sixteenth Annual Conference on Computational Learning Theory (COLT) , 2003.	ps gz
Kernel Design using Boosting Koby Crammer, Joseph Keshet and Yoram Singer Proceedings of the Fifteenth Annual Conference on Neural Information Processing Systems (NIPS), 2002.	ps gz pdf
Margin Analysis of the LVQ Algorithm Koby Crammer, Ran Gilad-Bachrach, Amir Navot and Naftali Tishby Proceedings of the Fifteenth Annual Conference on Neural Information Processing Systems (NIPS), 2002.	ps gz pdf long:ps long:gz
A New Family of Online Algorithms for Category Ranking Koby Crammer and Yoram Singer Proceedings of the 25rd Conference on Research and Development in Information Retrieval (SIGIR), 2002.	ps gz
PRanking with Ranking Koby Crammer and Yoram Singer Proceedings of the Fourteenth Annual Conference on Neural Information Processing Systems (NIPS), 2001.	ps gz
Ultraconservative Online Algorithms for Multiclass Problems Koby Crammer and Yoram Singer Proceedings of the Fourteenth Annual Conference on Computational Learning Theory (COLT) , 2001.	ps gz
Improved Output Coding for Classification Using Continuous Relaxation Koby Crammer and Yoram Singer Proceedings of the Thirteen Annual Conference on Neural Information Processing Systems (NIPS), 2000.	ps gz pdf
On the Learnability and Design of Output Codes for Multiclass Problems Koby Crammer and Yoram Singer Proceedings of the Thirteen Annual Conference on Computational Learning Theory (COLT) , 2000.	ps gz pdf

Loss-Sensitive Discriminative Training of Machine Transliteration Models Kedar Bellare, Koby Crammer and Dayne Freitag . NAACL Student Research Workshop poster, 2009	pdf
Scalable Large-Margin Online Learning for Structured Classification K. Crammer, R. McDonald, and F. Pereira Technical Report. Department of Computer and Information Science, University of Pennsylvania, 2005	pdf
An Apparatus for General Discriminative Categorization with Kernel Machines Koby Crammer and Yoram Singer Poster. Presented at the Sixteenth Annual Conference on Computational Learning Theory (COLT) , 2003.