Multiclass Learning by Probabilistic Embeddings. - Ofer Dekel; Yoram Singer (NIPS, 2002)

Smooth e-Intensive Regression by Loss Symmetrization. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (COLT, 2003)

Log-Linear Models for Label Ranking. - Ofer Dekel; Christopher D. Manning; Yoram Singer (NIPS, 2003)

Online Passive-Aggressive Algorithms. - Shai Shalev-Shwartz; Koby Crammer; Ofer Dekel; Yoram Singer (NIPS, 2003)

Large margin hierarchical classification. - Ofer Dekel; Joseph Keshet; Yoram Singer (ICML, 2004)

An Online Algorithm for Hierarchical Phoneme Classification. - Ofer Dekel; Joseph Keshet; Yoram Singer (MLMI, 2004)

The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (NIPS, 2004)

Data-Driven Online to Batch Conversions. - Ofer Dekel; Yoram Singer (NIPS, 2005)

The Forgetron: A Kernel-Based Perceptron on a Fixed Budget. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (NIPS, 2005)

Smooth epsiloon-Insensitive Regression by Loss Symmetrization. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (J. Mach. Learn. Res., 2005)

Online Multitask Learning. - Ofer Dekel; Philip M. Long; Yoram Singer (COLT, 2006)

Support Vector Machines on a Budget. - Ofer Dekel; Yoram Singer (NIPS, 2006)

Online Passive-Aggressive Algorithms. - Koby Crammer; Ofer Dekel; Joseph Keshet; Shai Shalev-Shwartz; Yoram Singer (J. Mach. Learn. Res., 2006)

A Boosting Algorithm for Label Covering in Multilabel Problems. - Yonatan Amit; Ofer Dekel; Yoram Singer (AISTATS, 2007)

Online Learning of Multiple Tasks with a Shared Loss. - Ofer Dekel; Philip M. Long; Yoram Singer (J. Mach. Learn. Res., 2007)

Endowing online prediction algorithms with the ability to generalize (יכולת הכללה באלגוריתמים לומדים מקוונים.). - Ofer Dekel (2007)

Learning to classify with missing and corrupted features. - Ofer Dekel; Ohad Shamir (ICML, 2008)

From Online to Batch Learning with Cutoff-Averaging. - Ofer Dekel (NIPS, 2008)

The Forgetron: A Kernel-Based Perceptron on a Budget. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (SIAM J. Comput., 2008)

Vox Populi: Collecting High-Quality Labels from a Crowd. - Ofer Dekel; Ohad Shamir (COLT, 2009)

Good learners for evil teachers. - Ofer Dekel; Ohad Shamir (ICML, 2009)

Distribution-Calibrated Hierarchical Classification. - Ofer Dekel (NIPS, 2009)

Individual sequence prediction using memory-efficient context trees. - Ofer Dekel; Shai Shalev-Shwartz; Yoram Singer (IEEE Trans. Inf. Theory, 2009)

Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback. - Alekh Agarwal; Ofer Dekel; Lin Xiao (COLT, 2010)

Robust Selective Sampling from Single and Multiple Teachers. - Ofer Dekel; Claudio Gentile; Karthik Sridharan (COLT, 2010)

Robust Distributed Online Prediction - Ofer Dekel; Ran Gilad-Bachrach; Ohad Shamir; Lin Xiao (CoRR, 2010)

Incentive compatible regression learning. - Ofer Dekel; Felix A. Fischer; Ariel D. Procaccia (J. Comput. Syst. Sci., 2010)

Multiclass-Multilabel Classification with More Classes than Examples. - Ofer Dekel; Ohad Shamir (AISTATS, 2010)

Learning to classify with missing and corrupted features. - Ofer Dekel; Ohad Shamir; Lin Xiao (Mach. Learn., 2010)

Optimal Distributed Online Prediction. - Ofer Dekel; Ran Gilad-Bachrach; Ohad Shamir; Lin Xiao (ICML, 2011)

Bundle Selling by Online Estimation of Valuation Functions. - Daniel Vainsencher; Ofer Dekel; Shie Mannor (ICML, 2011)

Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret. - Ofer Dekel; Ambuj Tewari; Raman Arora (ICML, 2012)

Deterministic MDPs with Adversarial Rewards and Bandit Feedback. - Raman Arora; Ofer Dekel; Ambuj Tewari (UAI, 2012)

Selective sampling and active learning from single and multiple teachers. - Ofer Dekel; Claudio Gentile; Karthik Sridharan (J. Mach. Learn. Res., 2012)

Optimal Distributed Online Prediction Using Mini-Batches. - Ofer Dekel; Ran Gilad-Bachrach; Ohad Shamir; Lin Xiao (J. Mach. Learn. Res., 2012)

There's a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems. - Ofer Dekel; Ohad Shamir (AISTATS, 2012)

Better Rates for Any Adversarial Deterministic MDP. - Ofer Dekel; Elad Hazan (ICML (3), 2013)

Online Learning with Switching Costs and Other Adaptive Adversaries. - Nicolò Cesa-Bianchi; Ofer Dekel; Ohad Shamir (NIPS, 2013)

Bandits with Switching Costs: T^{2/3} Regret. - Ofer Dekel; Jian Ding; Tomer Koren; Yuval Peres (CoRR, 2013)

Online Learning with Composite Loss Functions. - Ofer Dekel; Jian Ding; Tomer Koren; Yuval Peres (COLT, 2014)

The Blinded Bandit: Learning with Adaptive Feedback. - Ofer Dekel; Elad Hazan; Tomer Koren (NIPS, 2014)

Bandits with switching costs: T2/3 regret. - Ofer Dekel; Jian Ding; Tomer Koren; Yuval Peres (STOC, 2014)

Online Learning with Feedback Graphs: Beyond Bandits. - Noga Alon; Nicolò Cesa-Bianchi; Ofer Dekel; Tomer Koren (COLT, 2015)

Bandit Convex Optimization: ( sqrt{T} ) Regret in One Dimension. - Sébastien Bubeck; Ofer Dekel; Tomer Koren; Yuval Peres (COLT, 2015)

Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff. - Ofer Dekel; Ronen Eldan; Tomer Koren (NIPS, 2015)

Linear Learning with Sparse Data. - Ofer Dekel (CoRR, 2016)

Adaptive Neural Networks for Efficient Inference. - Tolga Bolukbasi; Joseph Wang 001; Ofer Dekel; Venkatesh Saligrama (ICML, 2017)

Machine learning on the edge. - Ofer Dekel (TIML@ISCA, 2017)

Online Learning with a Hint. - Ofer Dekel; Arthur Flajolet; Nika Haghtalab; Patrick Jaillet (NIPS, 2017)

Adaptive Neural Networks for Fast Test-Time Prediction. - Tolga Bolukbasi; Joseph Wang 001; Ofer Dekel; Venkatesh Saligrama (CoRR, 2017)

Learning SMaLL Predictors. - Vikas K. Garg 001; Ofer Dekel; Lin Xiao (NeurIPS, 2018)

Sparse Multi-Prototype Classification. - Vikas K. Garg 001; Lin Xiao; Ofer Dekel (UAI, 2018)

Blockbuster, Part 1: Block-level AI Operator Fusion. - Ofer Dekel (CoRR, 2025)