Alon Cohen

22 papers · 2015–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (14) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (8) 🏃 Academic Marathon (10) 🤝 Dynamic Duo (14) 🔬 Deep Specialist (10) 💎 Century Club (22) 🗃️ Keyword Collector (81) 📈 Trend Setter 🔥 Unstoppable (11)

Conferences

ICML (9) COLT (4) NIPS (4) AAAI (1) AISTATS (1) IJCAI (1) NAACL (1) UAI (1)

Top co-authors

Yishay Mansour (14) Tomer Koren (12) Haim Kaplan (5) Tamir Hazan (3) Asaf Cassel (3) Shay Moran (3) Avinatan Hassidim (3) Aviv Rosenberg (2) Amit Daniely (2) Orin Levy (2)

Keywords

regret bound (9) online learning (5) reinforcement learning (4) markov decision process (3) optimal policy (3) stochastic optimization (3) frank-wolfe algorithm (2) online algorithm (2) stochastic shortest path (2) bandit feedback (2) minimax regret (2) multiclass classification (2) apprenticeship learning (2) regret minimization (2) linear quadratic regulator (2) multi-armed bandit (2) sample complexity (1) sequential decision making (1) policy evaluation (1) assignment problem (1)

Papers

Locally Optimal Descent for Dynamic Stepsize Scheduling AISTATS 2025

Eluder-based Regret for Stochastic Contextual MDPs ICML 2024

Fast Rates for Bandit PAC Multiclass Classification NIPS 2024

Rate-Optimal Policy Optimization for Linear Markov Decision Processes ICML 2024

The Real Price of Bandit Information in Multiclass Classification COLT 2024

Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation ICML 2023

Efficient Online Linear Control with Stochastic Convex Costs and Unknown Dynamics COLT 2022

Asynchronous Stochastic Optimization Robust to Arbitrary Delays NIPS 2021

Minimax Regret for Stochastic Shortest Path NIPS 2021

Online Markov Decision Processes with Aggregate Bandit Feedback COLT 2021

Learning and Evaluating a Differentially Private Pre-trained Language Model NAACL 2021

Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently ICML 2020

Apprenticeship Learning via Frank-Wolfe AAAI 2020

Unknown mixing times in apprenticeship and reinforcement learning UAI 2020

Near-optimal Regret Bounds for Stochastic Shortest Path ICML 2020

Learning to Screen NIPS 2019

Learning Linear-Quadratic Regulators Efficiently with only $\sqrtT$ Regret ICML 2019

Online Linear Quadratic Control ICML 2018

Planning and Learning with Stochastic Action Sets IJCAI 2018

Tight Bounds for Bandit Combinatorial Optimization COLT 2017

Online Learning with Feedback Graphs Without the Graphs ICML 2016

Following the Perturbed Leader for Online Structured Learning ICML 2015