| 2022 | ICLR | Weighted Training for Cross-Task Learning. | Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J. Su |
| 2018 | ALT | A Better Resource Allocation Algorithm with Semi-Bandit Feedback. | Yuval Dagan, Koby Crammer |
| 2016 | SIGIR | That's Not My Question: Learning to Weight Unmatched Terms in CQA Vertical Search. | Boaz Petersil, Avihai Mejer, Idan Szpektor, Koby Crammer |
| 2015 | AAAI | Outlier-Robust Convex Segmentation. | Itamar Katz, Koby Crammer |
| 2015 | AISTATS | Convex Multi-Task Learning by Clustering. | Aviad Barzilai, Koby Crammer |
| 2015 | ISIT | In-memory hamming similarity computation in resistive arrays. | Yuval Cassuto, Koby Crammer |
| 2015 | ITA | Belief flows for robust online learning. | Pedro A. Ortega, Koby Crammer, Daniel D. Lee |
| 2014 | AISTATS | Doubly Aggressive Selective Sampling Algorithms for Classification. | Koby Crammer |
| 2014 | AISTATS | Selective Sampling with Drift. | Edward Moroshko, Koby Crammer |
| 2014 | AISTATS | Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. | Asaf Noy, Koby Crammer |
| 2014 | ICASSP | Non-parallel voice conversion using joint optimization of alignment by temporal context and spectral distortion. | Hadas Benisty, David Malah, Koby Crammer |
| 2014 | ICML | Concept Drift Detection Through Resampling. | Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer |
| 2014 | ICML | Prediction with Limited Advice and Multiarmed Bandits with Paid Observations. | Yevgeny Seldin, Peter L. Bartlett, Koby Crammer, Yasin Abbasi-Yadkori |
| 2014 | UAI | Optimal Resource Allocation with Semi-Bandit Feedback. | Tor Lattimore, Koby Crammer, Csaba Szepesvri |
| 2013 | AISTATS | A Last-Step Regression Algorithm for Non-Stationary Online Learning. | Edward Moroshko, Koby Crammer |
| 2013 | COLT | Open Problem: Adversarial Multiarmed Bandits with Limited Advice. | Yevgeny Seldin, Koby Crammer, Peter L. Bartlett |
| 2013 | IJCAI | Hartigan's K-Means Versus Lloyd's K-Means - Is It Time for a Change? | Noam Slonim, Ehud Aharoni, Koby Crammer |
| 2013 | IJCAI | Multi Class Learning with Individual Sparsity. | Ben Zion Vatashsky, Koby Crammer |
| 2012 | ALT | Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic Regret. | Edward Moroshko, Koby Crammer |
| 2012 | COLING | Metric Learning for Graph-Based Domain Adaptation. | Paramveer S. Dhillon, Partha Pratim Talukdar, Koby Crammer |
| 2012 | ICASSP | New ℌ | Koby Crammer, Alex Kulesza, Mark Dredze |
| 2012 | ICASSP | Online discriminative learning of phoneme recognition via collections of generalized linear models. | Koby Crammer, Daniel D. Lee |
| 2012 | ICML | Adaptive Regularization for Similarity Measures. | Koby Crammer, Gal Chechik |
| 2012 | NAACL | Training Dependency Parser Using Light Feedback. | Avihai Mejer, Koby Crammer |
| 2012 | NAACL | Are You Sure? Confidence in Prediction of Dependency Tree Edges. | Avihai Mejer, Koby Crammer |
| 2011 | ALT | Re-adapting the Regularization of Weights for Non-stationary Regression. | Nina Vaits, Koby Crammer |
| 2011 | ICML | Multiclass Classification with Bandit Feedback using Adaptive Regularization. | Koby Crammer, Claudio Gentile |
| 2011 | IJCAI | Active Online Classification via Information Maximization. | Noam Slonim, Elad Yom-Tov, Koby Crammer |
| 2011 | KDD | Trading representability for scalability: adaptive multi-hyperplane machine for nonlinear classification. | Zhuang Wang, Nemanja Djuric, Koby Crammer, Slobodan Vucetic |
| 2010 | ACL | Learning Better Data Representation Using Inference-Driven Metric Learning. | Paramveer S. Dhillon, Partha Pratim Talukdar, Koby Crammer |
| 2010 | COLT | Regret Minimization With Concept Drift. | Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jennifer Wortman Vaughan |
| 2010 | EMNLP | Confidence in Structured-Prediction Using Confidence-Weighted Models. | Avihai Mejer, Koby Crammer |
| 2010 | ICASSP | Efficient online learning with individual learning-rates for phoneme sequence recognition. | Koby Crammer |
| 2010 | ICML | Multi-Class Pegasos on a Budget. | Zhuang Wang, Koby Crammer, Slobodan Vucetic |
| 2009 | EMNLP | Multi-Class Confidence Weighted Algorithms. | Koby Crammer, Mark Dredze, Alex Kulesza |
| 2009 | ICDM | Resolving Identity Uncertainty with Learned Random Walks. | Ted Sandler, Lyle H. Ungar, Koby Crammer |
| 2009 | Interspeech | How to loose confidence: probabilistic linear machines for multiclass classification. | Hui Lin, Jeff A. Bilmes, Koby Crammer |
| 2009 | NAACL | Loss-Sensitive Discriminative Training of Machine Transliteration Models. | Kedar Bellare, Koby Crammer, Dayne Freitag |
| 2008 | ACL | Advanced Online Learning for Natural Language Processing. | Koby Crammer |
| 2008 | ACL | Active Learning with Confidence. | Mark Dredze, Koby Crammer |
| 2008 | EMNLP | One-Class Clustering in the Text Domain. | Ron Bekkerman, Koby Crammer |
| 2008 | EMNLP | Online Methods for Multi-Domain Learning and Adaptation. | Mark Dredze, Koby Crammer |
| 2008 | ICML | A rate-distortion one-class model and its applications to clustering. | Koby Crammer, Partha Pratim Talukdar, Fernando C. N. Pereira |
| 2008 | ICML | Confidence-weighted linear classification. | Mark Dredze, Koby Crammer, Fernando Pereira |
| 2007 | Interspeech | A conservative aggressive subspace tracker. | Koby Crammer |
| 2006 | AAAI | Robust Support Vector Machine Training via Convex Outlier Ablation. | Linli Xu, Koby Crammer, Dale Schuurmans |
| 2006 | COLT | Online Tracking of Linear Subspaces. | Koby Crammer |
| 2006 | ICASSP | Room Impulse Response Estimation using Sparse Online Prediction and Absolute Loss. | Koby Crammer, Daniel D. Lee |
| 2006 | UAI | Discriminative Learning via Semidefinite Probabilistic Models. | Koby Crammer, Amir Globerson |
| 2005 | ACL | Online Large-Margin Training of Dependency Parsers. | Ryan T. McDonald, Koby Crammer, Fernando C. N. Pereira |
| 2005 | COLT | Loss Bounds for Online Category Ranking. | Koby Crammer, Yoram Singer |
| 2005 | NAACL | Flexible Text Segmentation with Structured Multilabel Classification. | Ryan T. McDonald, Koby Crammer, Fernando Pereira |
| 2004 | ICML | A needle in a haystack: local one-class optimization. | Koby Crammer, Gal Chechik |
| 2003 | COLT | Learning Algorithm for Enclosing Points in Bregmanian Spheres. | Koby Crammer, Yoram Singer |
| 2002 | SIGIR | A new family of online algorithms for category ranking. | Koby Crammer, Yoram Singer |
| 2001 | COLT | Ultraconservative Online Algorithms for Multiclass Problems. | Koby Crammer, Yoram Singer |
| 2000 | COLT | On the Learnability and Design of Output Codes for Multiclass Problems. | Koby Crammer, Yoram Singer |