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All publications by Koby Crammer
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Linear Multi-Resource Allocation with Semi-Bandit Feedback
Tor Lattimore, Koby Crammer and Csaba Szepesvari
Advances in Neural Information Processing Systems 28, 2015


Concept Drift Detection Through Resampling
Maayan Harel, Shie Mannor, Ran El-yaniv and Koby Crammer
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Prediction with Limited Advice and Multiarmed Bandits with Paid Observations
Yevgeny Seldin, Peter Bartlett, Koby Crammer and Yasin Abbasi-yadkori
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Learning Multiple Tasks in Parallel with a Shared Annotator
Haim Cohen and Koby Crammer
Advances in Neural Information Processing Systems 27, 2014


Learning Multiple Tasks using Shared Hypotheses
Koby Crammer and Yishay Mansour
Advances in Neural Information Processing Systems 25, 2012


Volume Regularization for Binary Classification
Koby Crammer and Tal Wagner
Advances in Neural Information Processing Systems 25, 2012


Adaptive Regularization for Weight Matrices
Koby Crammer and Gal Chechik
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


A Simple Geometric Interpretation of SVM using Stochastic Adversaries
Roi Livni, Koby Crammer and Amir Globerson
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Multiclass Classification with Bandit Feedback using Adaptive Regularization
Koby Crammer and Claudio Gentile
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Multi-Class Pegasos on a Budget
Zhuang Wang, Koby Crammer and Slobodan Vucetic
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


New Adaptive Algorithms for Online Classification
Francesco Orabona and Koby Crammer
Advances in Neural Information Processing Systems 23, 2010


Learning via Gaussian Herding
Koby Crammer and Daniel D. Lee
Advances in Neural Information Processing Systems 23, 2010


Exploiting Feature Covariance in High-Dimensional Online Learning
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul and Fernando Pereira
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Adaptive Regularization of Weight Vectors
Koby Crammer, Alex Kulesza and Mark Dredze
Advances in Neural Information Processing Systems 22, 2009


Gaussian Margin Machines
Koby Crammer, Mehryar Mohri and Fernando Pereira
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Confidence-weighted linear classification
Mark Dredze, Koby Crammer and Fernando Pereira
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


A rate-distortion one-class model and its applications to clustering
Koby Crammer, Partha P. Talukdar and Fernando Pereira
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Learning from Multiple Sources
Koby Crammer, Michael Kearns and Jennifer Wortman
Journal of Machine Learning Research, 2008


Exact Convex Confidence-Weighted Learning
Koby Crammer, Mark Dredze and Fernando Pereira
Advances in Neural Information Processing Systems 21, 2008


Learning Bounds for Domain Adaptation
John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira and Jennifer Wortman
Advances in Neural Information Processing Systems 20, 2007


Analysis of Representations for Domain Adaptation
Shai Ben-david, John Blitzer, Koby Crammer and Fernando Pereira
Advances in Neural Information Processing Systems 19, 2006


Learning from Multiple Sources
Koby Crammer, Michael Kearns and Jennifer Wortman
Advances in Neural Information Processing Systems 19, 2006


Online Passive-Aggressive Algorithms
Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2006


A needle in a haystack: local one-class optimization
Koby Crammer and Gal Chechik
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities
Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia and Yoram Singer
Advances in Neural Information Processing Systems 17, 2004


Online Passive-Aggressive Algorithms
Shai Shalev-shwartz, Koby Crammer, Ofer Dekel and Yoram Singer
Advances in Neural Information Processing Systems 16, 2003


Online Classification on a Budget
Koby Crammer, Jaz Kandola and Yoram Singer
Advances in Neural Information Processing Systems 16, 2003


A Family of Additive Online Algorithms for Category Ranking
Koby Crammer and Yoram Singer
Journal of Machine Learning Research, 2003


Ultraconservative Online Algorithms for Multiclass Problems
Koby Crammer and Yoram Singer
Journal of Machine Learning Research, 2003


Margin Analysis of the LVQ Algorithm
Koby Crammer, Ran Gilad-bachrach, Amir Navot and Naftali Tishby
Advances in Neural Information Processing Systems 15, 2002


Kernel Design Using Boosting
Koby Crammer, Joseph Keshet and Yoram Singer
Advances in Neural Information Processing Systems 15, 2002


Pranking with Ranking
Koby Crammer and Yoram Singer
Advances in Neural Information Processing Systems 14, 2001


On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines
Koby Crammer and Yoram Singer
Journal of Machine Learning Research, 2001