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Ofer Dekel

20 papers · 2005–2018 · 5 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (5) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (11) 🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (13) 🌟 Keyword Trendsetter Combo (6) 🌱 Topic Pioneer πŸ† Keyword Champion πŸš€ Conference Pioneer πŸ’Ž Century Club (20) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (89) πŸ”₯ Unstoppable (6)

Conferences

NIPS (8) JMLR (5) COLT (3) AISTATS (2) ICML (2)

Top co-authors

Tomer Koren (5) Ohad Shamir (4) Yoram Singer (4) NicolΓ² Cesa-bianchi (2) Elad Hazan (2) Shai Shalev-shwartz (2) Yuval Peres (2) Lin Xiao (2) Karthik Sridharan (1) Vikas Garg (1)

Keywords

online learning (12) regret bound (8) bandit feedback (3) regret minimization (3) multi-armed bandit (3) minimax regret (3) bandit convex optimization (2) stochastic optimization (2) binary classification (2) sparse classifier (2) gradient descent (2) loss function (2) sample complexity (1) weakly supervised learning (1) model selection (1) sequential decision making (1) hierarchical classification (1) multi-task learning (1) active learning (1) convex optimization (1)

Papers

Learning SMaLL Predictors NIPS 2018
Online Learning with a Hint NIPS 2017
Adaptive Neural Networks for Efficient Inference ICML 2017
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff NIPS 2015
Online Learning with Feedback Graphs: Beyond Bandits COLT 2015
Bandit Convex Optimization: \sqrtT Regret in One Dimension COLT 2015
The Blinded Bandit: Learning with Adaptive Feedback NIPS 2014
Online Learning with Composite Loss Functions COLT 2014
Online Learning with Switching Costs and Other Adaptive Adversaries NIPS 2013
Better Rates for Any Adversarial Deterministic MDP ICML 2013
Selective Sampling and Active Learning from Single and Multiple Teachers JMLR 2012
There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems AISTATS 2012
Optimal Distributed Online Prediction Using Mini-Batches JMLR 2012
Multiclass-Multilabel Classification with More Classes than Examples AISTATS 2010
Distribution-Calibrated Hierarchical Classification NIPS 2009
From Online to Batch Learning with Cutoff-Averaging NIPS 2008
Online Learning of Multiple Tasks with a Shared Loss JMLR 2007
Online Passive-Aggressive Algorithms JMLR 2006
Support Vector Machines on a Budget NIPS 2006
Smooth Ξ΅-Insensitive Regression by Loss Symmetrization JMLR 2005