Elad Hazan - Publications

Affiliations: 
Computer Science Princeton University, Princeton, NJ 

56 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2016 Hazan E, Kale S, Warmuth MK. Learning rotations with little regret Machine Learning. 1-20. DOI: 10.1007/s10994-016-5548-x  0.56
2015 Ben-Tal A, Hazan E, Koren T, Mannor S. Oracle-based robust optimization via online learning Operations Research. 63: 628-638. DOI: 10.1287/opre.2015.1374  0.56
2015 Hazan E, Kale S. An Online Portfolio Selection Algorithm With Regret Logarithmic In Price Variation Mathematical Finance. 25: 288-310. DOI: 10.1111/mafi.12006  0.56
2015 Hazan E, Koren T. A linear-time algorithm for trust region problems Mathematical Programming. DOI: 10.1007/s10107-015-0933-y  0.56
2015 Garber D, Hazan E. Sublinear time algorithms for approximate semidefinite programming Mathematical Programming. DOI: 10.1007/s10107-015-0932-z  0.56
2015 Beygelzimer A, Hazan E, Kale S, Luo H. Online gradient boosting Advances in Neural Information Processing Systems. 2015: 2458-2466.  0.56
2015 Anava O, Hazan E, Mannor S. Online learning for adversaries with memory: Price of past mistakes Advances in Neural Information Processing Systems. 2015: 784-792.  0.56
2015 Hazan E, Levy KY, Shalev-Shwartz S. Beyond convexity: Stochastic quasi-convex optimization Advances in Neural Information Processing Systems. 2015: 1594-1602.  0.56
2014 Hazan E, Levy KY. Bandit convex optimization: Towards tight bounds Advances in Neural Information Processing Systems. 1: 784-792.  0.56
2014 Hazan E, Koren T, Levy KY. Logistic regression: Tight bounds for stochastic and online optimization Journal of Machine Learning Research. 35: 197-209.  0.56
2014 Hazan E, Karnin Z, Meka R. Volumetric spanners: An efficient exploration basis for learning Journal of Machine Learning Research. 35: 408-422.  0.56
2014 Hazan E, Kale S. Beyond the regret minimization barrier: Optimal algorithms for stochastic strongly-convex optimization Journal of Machine Learning Research. 15: 2489-2512.  0.56
2014 Dekel O, Hazan E, Koren T. The blinded bandit: Learning with adaptive feedback Advances in Neural Information Processing Systems. 2: 1610-1618.  0.56
2014 Hazan E, Karnin Z. Hard-margin active linear regression 31st International Conference On Machine Learning, Icml 2014. 3: 2492-2500.  0.56
2013 Garber D, Hazan E. Adaptive universal linear filtering Ieee Transactions On Signal Processing. 61: 1595-1604. DOI: 10.1109/TSP.2012.2234742  0.56
2013 Garber D, Hazan E. Playing non-linear games with linear oracles Proceedings - Annual Ieee Symposium On Foundations of Computer Science, Focs. 420-428. DOI: 10.1109/FOCS.2013.52  0.56
2013 Dekel O, Hazan E. Better rates for any adversarial deterministic MDP 30th International Conference On Machine Learning, Icml 2013. 1712-1720.  0.56
2013 Anava O, Hazan E, Mannor S, Shamir O. Online learning for time series prediction Journal of Machine Learning Research. 30: 172-184.  0.56
2012 Clarkson KL, Hazan E, Woodruff DP. Sublinear optimization for machine learning Journal of the Acm. 59. DOI: 10.1145/2371656.2371658  0.56
2012 Abernethy JD, Hazan E, Rakhlin A. Interior-point methods for full-information and bandit online learning Ieee Transactions On Information Theory. 58: 4164-4175. DOI: 10.1109/TIT.2012.2192096  0.56
2012 Hazan E, Karnin Z. A provably efficient simplex algorithm for classification Advances in Neural Information Processing Systems. 1: 629-637.  0.56
2012 Hazan E, Koren T. Linear regression with limited observation Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 807-814.  0.56
2012 Hazan E, Kale S. Projection-free online learning Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 521-528.  0.56
2012 Hazan E, Kale S. Online submodular minimization Journal of Machine Learning Research. 13: 2903-2922.  0.56
2012 Hazan E, Kale S, Shalev-Shwartz S. Near-optimal algorithms for online matrix prediction Journal of Machine Learning Research. 23: 38.1-38.13.  0.56
2012 Hazan E, Kakade S. (Weak) calibration is computationally hard Journal of Machine Learning Research. 23: 3.1-3.10.  0.56
2011 Hazan E, Krauthgamer R. How hard is it to approximate the best nash equilibrium? Siam Journal On Computing. 40: 79-91. DOI: 10.1137/090766991  0.56
2011 Hazan E, Kale S. NEWTRON: An efficient bandit algorithm for online multiclass prediction Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011 0.56
2011 Hazan E, Koren T, Srebro N. Beating SGD: Learning SVMs in sublinear time Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011 0.56
2011 Garber D, Hazan E. Approximating semidefinite programs in sublinear time Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011 0.56
2011 Duchi J, Hazan E, Singer Y. Adaptive subgradient methods for online learning and stochastic optimization Journal of Machine Learning Research. 12: 2121-2159.  0.56
2011 Hazan E, Kale S. Better algorithms for benign bandits Journal of Machine Learning Research. 12: 1287-1311.  0.56
2011 Hazan E, Kale S. Beyond the regret minimization barrier: An optimal algorithm for stochastic strongly-convex optimization Journal of Machine Learning Research. 19: 421-436.  0.56
2011 Hazan E, Kale S. A simple multi-armed bandit algorithm with optimal variation-bounded regret Journal of Machine Learning Research. 19: 817-819.  0.56
2011 Abernethy J, Bartlett PL, Hazan E. Blackwell Approachability and no-regret learning are equivalent Journal of Machine Learning Research. 19: 27-46.  0.56
2011 Duchi J, Hazan E, Singer Y. Adaptive subgradient methods for online learning and stochastic optimization Journal of Machine Learning Research. 12: 2121-2159.  0.56
2010 Arora S, Hazan E, Kale S. O(√log n) approximation to sparsest cut in õ(n2) time Siam Journal On Computing. 39: 1748-1771. DOI: 10.1137/080731049  0.56
2010 Hazan E, Kale S. Extracting certainty from uncertainty: Regret bounded by variation in costs Machine Learning. 80: 165-188. DOI: 10.1007/s10994-010-5175-x  0.56
2010 Hazan E, Kale S, Warmuth MK. On-line variance minimization in O(n2) per trial? Colt 2010 - the 23rd Conference On Learning Theory. 314-315.  0.56
2009 Hazan E, Seshadhri C. Efficient learning algorithms for changing environments Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 393-400. DOI: 10.1145/1553374.1553425  0.56
2009 Hazan E, Kale S. Computational equivalence of fixed points and no regret algorithms, and convergence to equilibria Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 0.56
2009 Hazan E, Kale S. On stochastic and worst-case models for investing Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 709-717.  0.56
2009 Bartlett PL, Hazan E, Rakhlin A. Adaptive online gradient descent Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 0.56
2008 Hazan E. Sparse approximate solutions to semidefinite programs Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4957: 306-316. DOI: 10.1007/978-3-540-78773-0_27  0.56
2008 Abernethy J, Hazan E, Rakhlin A. Competing in the dark: An efficient algorithm for bandit linear optimization 21st Annual Conference On Learning Theory, Colt 2008. 263-273.  0.56
2007 Hazan E, Agarwal A, Kale S. Logarithmic regret algorithms for online convex optimization Machine Learning. 69: 169-192. DOI: 10.1007/s10994-007-5016-8  0.56
2007 Hazan E, Megiddo N. Online learning with prior knowledge Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4539: 499-513.  0.56
2006 Halperin E, Hazan E. HAPLOFREQ--estimating haplotype frequencies efficiently. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 13: 481-500. PMID 16597253 DOI: 10.1089/cmb.2006.13.481  0.56
2006 Agarwal A, Hazan E, Kale S, Schapire RE. Algorithms for portfolio management based on the Newton method Acm International Conference Proceeding Series. 148: 9-16. DOI: 10.1145/1143844.1143846  0.56
2006 Hazan E, Safra S, Schwartz O. On the complexity of approximating k-Set Packing Computational Complexity. 15: 20-39. DOI: 10.1007/s00037-006-0205-6  0.56
2006 Arora S, Hazan E, Kale S. A fast random sampling algorithm for sparsifying matrices Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4110: 272-279.  0.56
2005 Arora S, Berger E, Hazan E, Kindler G, Safra M. On non-approximability for quadratic programs Proceedings - Annual Ieee Symposium On Foundations of Computer Science, Focs. 2005: 206-215. DOI: 10.1109/SFCS.2005.57  0.56
2005 Arora S, Hazan E, Kale S. Fast algorithms for approximate semidefinite programming using the multiplicative weights update method Proceedings - Annual Ieee Symposium On Foundations of Computer Science, Focs. 2005: 339-348. DOI: 10.1109/SFCS.2005.35  0.56
2005 Halperin E, Hazan E. HAPLOFREQ - Estimating haplotype frequencies efficiently Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science). 3500: 553-568.  0.56
2004 Arora S, Hazan E, Kale S. O(√log n) approximation to SPARSEST CUT in Õ(n 2) time Proceedings - Annual Ieee Symposium On Foundations of Computer Science, Focs. 238-247.  0.56
2003 Hazan E, Safra S, Schwartz O. On the complexity of approximating k-dimensional matching Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2764: 83-97.  0.56
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