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Ofer Dekel
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2010 – 2019
- 2018
- [c39]Vikas K. Garg, Ofer Dekel, Lin Xiao:
Learning SMaLL Predictors. NeurIPS 2018: 9143-9153 - [c38]Vikas K. Garg, Lin Xiao, Ofer Dekel:
Sparse Multi-Prototype Classification. UAI 2018: 704-714 - [i12]Vikas K. Garg, Ofer Dekel, Lin Xiao:
Learning SMaLL Predictors. CoRR abs/1803.02388 (2018) - 2017
- [c37]Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama:
Adaptive Neural Networks for Efficient Inference. ICML 2017: 527-536 - [c36]Ofer Dekel:
Machine learning on the edge. TIML@ISCA 2017: 4 - [c35]Ofer Dekel, Arthur Flajolet, Nika Haghtalab, Patrick Jaillet:
Online Learning with a Hint. NIPS 2017: 5299-5308 - [i11]Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama:
Adaptive Neural Networks for Fast Test-Time Prediction. CoRR abs/1702.07811 (2017) - 2016
- [i10]Ofer Dekel:
Linear Learning with Sparse Data. CoRR abs/1612.09147 (2016) - 2015
- [c34]Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren:
Online Learning with Feedback Graphs: Beyond Bandits. COLT 2015: 23-35 - [c33]Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres:
Bandit Convex Optimization: \(\sqrt{T}\) Regret in One Dimension. COLT 2015: 266-278 - [c32]Ofer Dekel, Ronen Eldan, Tomer Koren:
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff. NIPS 2015: 2926-2934 - [i9]Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres:
Bandit Convex Optimization: sqrt{T} Regret in One Dimension. CoRR abs/1502.06398 (2015) - [i8]Noga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren:
Online Learning with Feedback Graphs: Beyond Bandits. CoRR abs/1502.07617 (2015) - 2014
- [c31]Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres:
Online Learning with Composite Loss Functions. COLT 2014: 1214-1231 - [c30]Ofer Dekel, Elad Hazan, Tomer Koren:
The Blinded Bandit: Learning with Adaptive Feedback. NIPS 2014: 1610-1618 - [c29]Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres:
Bandits with switching costs: T2/3 regret. STOC 2014: 459-467 - [i7]Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres:
Online Learning with Composite Loss Functions. CoRR abs/1405.4471 (2014) - 2013
- [c28]Ofer Dekel, Elad Hazan:
Better Rates for Any Adversarial Deterministic MDP. ICML (3) 2013: 675-683 - [c27]Nicolò Cesa-Bianchi, Ofer Dekel, Ohad Shamir:
Online Learning with Switching Costs and Other Adaptive Adversaries. NIPS 2013: 1160-1168 - [i6]Nicolò Cesa-Bianchi, Ofer Dekel, Ohad Shamir:
Online Learning with Switching Costs and Other Adaptive Adversaries. CoRR abs/1302.4387 (2013) - [i5]Ofer Dekel, Jian Ding, Tomer Koren, Yuval Peres:
Bandits with Switching Costs: T^{2/3} Regret. CoRR abs/1310.2997 (2013) - 2012
- [j9]Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao:
Optimal Distributed Online Prediction Using Mini-Batches. J. Mach. Learn. Res. 13: 165-202 (2012) - [j8]Ofer Dekel, Claudio Gentile, Karthik Sridharan:
Selective sampling and active learning from single and multiple teachers. J. Mach. Learn. Res. 13: 2655-2697 (2012) - [c26]Ofer Dekel, Ambuj Tewari, Raman Arora:
Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret. ICML 2012 - [c25]Raman Arora, Ofer Dekel, Ambuj Tewari:
Deterministic MDPs with Adversarial Rewards and Bandit Feedback. UAI 2012: 93-101 - [c24]Ofer Dekel, Ohad Shamir:
There's a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems. AISTATS 2012: 291-298 - [i4]Raman Arora, Ofer Dekel, Ambuj Tewari:
Deterministic MDPs with Adversarial Rewards and Bandit Feedback. CoRR abs/1210.4843 (2012) - 2011
- [c23]Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao:
Optimal Distributed Online Prediction. ICML 2011: 713-720 - [c22]Daniel Vainsencher, Ofer Dekel, Shie Mannor:
Bundle Selling by Online Estimation of Valuation Functions. ICML 2011: 1137-1144 - 2010
- [j7]Ofer Dekel, Felix A. Fischer, Ariel D. Procaccia:
Incentive compatible regression learning. J. Comput. Syst. Sci. 76(8): 759-777 (2010) - [j6]Ofer Dekel, Ohad Shamir, Lin Xiao:
Learning to classify with missing and corrupted features. Mach. Learn. 81(2): 149-178 (2010) - [c21]Alekh Agarwal, Ofer Dekel, Lin Xiao:
Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback. COLT 2010: 28-40 - [c20]Ofer Dekel, Claudio Gentile, Karthik Sridharan:
Robust Selective Sampling from Single and Multiple Teachers. COLT 2010: 346-358 - [c19]Ofer Dekel, Ohad Shamir:
Multiclass-Multilabel Classification with More Classes than Examples. AISTATS 2010: 137-144 - [i3]Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao:
Optimal Distributed Online Prediction using Mini-Batches. CoRR abs/1012.1367 (2010) - [i2]Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao:
Robust Distributed Online Prediction. CoRR abs/1012.1370 (2010)
2000 – 2009
- 2009
- [j5]Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer:
Individual sequence prediction using memory-efficient context trees. IEEE Trans. Inf. Theory 55(11): 5251-5262 (2009) - [c18]Ofer Dekel, Ohad Shamir:
Vox Populi: Collecting High-Quality Labels from a Crowd. COLT 2009 - [c17]Ofer Dekel, Ohad Shamir:
Good learners for evil teachers. ICML 2009: 233-240 - [c16]Ofer Dekel:
Distribution-Calibrated Hierarchical Classification. NIPS 2009: 450-458 - 2008
- [j4]Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer:
The Forgetron: A Kernel-Based Perceptron on a Budget. SIAM J. Comput. 37(5): 1342-1372 (2008) - [c15]Ofer Dekel, Ohad Shamir:
Learning to classify with missing and corrupted features. ICML 2008: 216-223 - [c14]Ofer Dekel:
From Online to Batch Learning with Cutoff-Averaging. NIPS 2008: 377-384 - [c13]Ofer Dekel, Felix A. Fischer, Ariel D. Procaccia:
Incentive compatible regression learning. SODA 2008: 884-893 - 2007
- [b1]Ofer Dekel:
Endowing online prediction algorithms with the ability to generalize (יכולת הכללה באלגוריתמים לומדים מקוונים.). Hebrew University of Jerusalem, Israel, 2007 - [j3]Ofer Dekel, Philip M. Long, Yoram Singer:
Online Learning of Multiple Tasks with a Shared Loss. J. Mach. Learn. Res. 8: 2233-2264 (2007) - [c12]Yonatan Amit, Ofer Dekel, Yoram Singer:
A Boosting Algorithm for Label Covering in Multilabel Problems. AISTATS 2007: 27-34 - [i1]Ofer Dekel, Felix A. Fischer, Ariel D. Procaccia:
Incentive Compatible Regression Learning. Computational Social Systems and the Internet 2007 - 2006
- [j2]Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer:
Online Passive-Aggressive Algorithms. J. Mach. Learn. Res. 7: 551-585 (2006) - [c11]Ofer Dekel, Philip M. Long, Yoram Singer:
Online Multitask Learning. COLT 2006: 453-467 - [c10]Ofer Dekel, Yoram Singer:
Support Vector Machines on a Budget. NIPS 2006: 345-352 - 2005
- [j1]Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer:
Smooth epsiloon-Insensitive Regression by Loss Symmetrization. J. Mach. Learn. Res. 6: 711-741 (2005) - [c9]Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer:
The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. NIPS 2005: 259-266 - [c8]Ofer Dekel, Yoram Singer:
Data-Driven Online to Batch Conversions. NIPS 2005: 267-274 - 2004
- [c7]Ofer Dekel, Joseph Keshet, Yoram Singer:
Large margin hierarchical classification. ICML 2004 - [c6]Ofer Dekel, Joseph Keshet, Yoram Singer:
An Online Algorithm for Hierarchical Phoneme Classification. MLMI 2004: 146-158 - [c5]Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer:
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees. NIPS 2004: 345-352 - 2003
- [c4]Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer:
Smooth e-Intensive Regression by Loss Symmetrization. COLT 2003: 433-447 - [c3]Ofer Dekel, Christopher D. Manning, Yoram Singer:
Log-Linear Models for Label Ranking. NIPS 2003: 497-504 - [c2]Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer:
Online Passive-Aggressive Algorithms. NIPS 2003: 1229-1236 - 2002
- [c1]Ofer Dekel, Yoram Singer:
Multiclass Learning by Probabilistic Embeddings. NIPS 2002: 945-952
Coauthor Index
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