Publications

Journal Papers

  • Ofer Dekel, Claudio Gentile, and Karthik Sridharan. Selective sampling and active learning from single and multiple teachers. Journal of Machine Learning Research, 13:2655-2697, 2012. PDF
  • Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, and Lin Xiao. Optimal distributed online prediction using mini-batches. Journal of Machine Learning Research, 13:165-202, 2012. PDF
  • Ofer Dekel, Felix Fischer, and Ariel D. Procaccia. Incentive compatible regression learning. Journal of Computer and System Sciences, 76:759-777, 2010. PDF
  • Ofer Dekel, Ohad Shamir, and Lin Xiao. Learning to classify with missing and corrupted features. Machine Learning Journal, 81:149-178, 2010. PDF
  • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. Individual sequence prediction using memory-efficient context trees. IEEE Transactions on Information Theory, 55(11):5251-5262, 2009. PDF
  • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. The Forgetron: A kernel-based perceptron on a budget. SIAM Journal on Computing, 37(5):1342-1372, 2008. PDF
  • Ofer Dekel, Philip M. Long, and Yoram Singer. Online learning of multiple tasks with a shared loss. Journal of Machine Learning Research, 8:2233-2264, 2007. PDF
  • Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, and Yoram Singer. Online passive-aggressive algorithms. Journal of Machine Learning Research, 7:551-585, 2006. PDF
  • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. Smooth epsilon-insensitive regression by loss symmetrization. Journal of Machine Learning Research, 6:711-741, 2005. PDF

Conference Papers

  • Ofer Dekel, Jian Ding, Tomer Koren, and Yuval Peres. Online Learning with Composite Loss Functions In Proceedings of the 27th Annual Conference on Learning Theory, 2014. PDF
  • Ofer Dekel, Jian Ding, Tomer Koren, and Yuval Peres. Bandits with Switching Costs: T^(2/3) Regret In Proceedings of the 46th Annual Symposium on the Theory of Computing, 2014. PDF
  • Nicolo Cesa-Bianchi, Ofer Dekel, and Ohad Shamir. Online Learning with Switching Costs and Other Adaptive Adversaries. In Advances in Neural Information Processing Systems 26, pages 1160-1168. Curran Associates, Inc., 2013. PDF
  • Ofer Dekel and Elad Hazan. Better Rates for Any Adversarial Deterministic MDP. In Proceedings of the Thirtieth Internation Conference on Machine Learning, 2013. PDF
  • Raman Arora, Ofer Dekel, and Ambuj Tewari. Deterministic MDPs with Adversarial Rewards and Bandit Feedback. In Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012. PDF
  • Raman Arora, Ofer Dekel, and Ambuj Tewari. Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, 2012. PDF
  • Ofer Dekel and Ohad Shamir. There's a Hole in My Dataspace. In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, JMLR: W&CP 22, 2012. PDF
  • Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, and Lin Xiao. Optimal distributed online prediction. In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. PDF
  • Daniel Vainsencher, Ofer Dekel, and Shie Mannor. Bundle selling by online estimation of valuation functions. In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. PDF
  • Alekh Agarwal, Ofer Dekel, and Lin Xiao. Optimal algorithms for online convex optimization with multi-point bandit feedback. In Proceedings of the Twenty-Third Annual Conference on Learning Theory, pages 28-40, 2010. PDF
  • Ofer Dekel, Claudio Gentile, and Karthik Sridharan. Robust selective sampling from single and multiple teachers. In Proceedings of the Twenty-Third Annual Conference on Learning Theory, pages 346-358, 2010. PDF
  • Ofer Dekel and Ohad Shamir. Multiclass-multilabel classification with more classes than examples. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, JMLR 9:137-144, 2010. PDF
  • Ofer Dekel. Distribution-calibrated hierarchical classification. In Advances in Neural Information Processing Systems 22, 2010. PDF
  • Ofer Dekel and Ohad Shamir. Vox populi: Collecting high-quality labels from a crowd. In Proceedings of the Twenty-Second Annual Conference on Learning Theory, 2009. PDF
  • Ofer Dekel and Ohad Shamir. Good learners for evil teachers. In Proceedings of the Twenty-Sixth International Conference on Machine Learning, pages 216-223, 2009. PDF
  • Ofer Dekel. From online to batch learning with cutoff averaging. In Advances in Neural Information Processing Systems 21, 2009. PDF
  • Ofer Dekel and Ohad Shamir. Learning to classify with missing and corrupted features. In Proceedings of the Twenty-Fifth International Conference on Machine Learning, 2008. PDF
  • Ofer Dekel, Felix Fischer, and Ariel Procaccia. Incentive compatible regression learning. In Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 884-893, 2008. PDF
  • Yonatan Amit, Ofer Dekel, and Yoram Singer. A boosting algorithm for label covering in multilabel problems. In Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007. PDF
  • Ofer Dekel and Yoram Singer. Support vector machines on a budget. In Advances in Neural Information Processing Systems 19, pages 345-352. MIT Press, 2007. PDF
  • Ofer Dekel, Philip M. Long, and Yoram Singer. Online multitask learning. In Proceedings of the Nineteenth Annual Conference on Learning Theory, pages 453-467. Springer LNAI 4005, 2006. PDF
  • Ofer Dekel and Yoram Singer. Data-driven online to batch conversions. In Advances in Neural Information Processing Systems 18, pages 267-274. MIT Press, 2006. PDF
  • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. The Forgetron: A kernel-based perceptron on a fixed budget. In Advances in Neural Information Processing Systems 18, pages 259-266. MIT Press, 2006. PDF
  • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. The power of selective memory: Self-bounded learning of prediction suffix trees. In Advances in Neural Information Processing Systems 17, pages 345-352. MIT Press, 2005. PDF
  • Ofer Dekel, Joseph Keshet, and Yoram Singer. An online algorithm for hierarchical phoneme classification. In Machine Learning for Multimodal Interaction: First International Workshop, pages 146-158. Springer LNAI 3361, 2005. PDF
  • Ofer Dekel, Joseph Keshet, and Yoram Singer. Large margin hierarchical classification. In Proceedings of the Twenty-First International Conference on Machine Learning, 2004. PDF
  • Ofer Dekel, Christopher Manning, and Yoram Singer. Log-linear models for label ranking. In Advances in Neural Information Processing Systems 16, 2004. PDF
  • Koby Crammer, Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. Online passive-aggressive algorithms. In Advances in Neural Information Processing Systems 16. MIT Press, 2004. PDF
  • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. Smooth epsilon-insensitive regression by loss symmetrization. In Proceedings of the Sixteenth Annual Conference on Computational Learning Theory, pages 433-447. Springer LNAI 2777, 2003. PDF
  • Ofer Dekel and Yoram Singer. Multiclass categorization by probabilistic embeddings. In Advances in Neural Information Processing Systems 15, pages 945-952. MIT Press, 2003. PDF