Alon Cohen

According to our database1, Alon Cohen authored at least 31 papers between 2013 and 2023.

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Bibliography

2023
Learning approximately optimal contracts.
Theor. Comput. Sci., November, 2023

Locally Optimal Descent for Dynamic Stepsize Scheduling.
CoRR, 2023

Rate-Optimal Policy Optimization for Linear Markov Decision Processes.
CoRR, 2023

APART: Diverse Skill Discovery using All Pairs with Ascending Reward and DropouT.
CoRR, 2023

Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation.
Proceedings of the International Conference on Machine Learning, 2023

2022
Counterfactual Optimism: Rate Optimal Regret for Stochastic Contextual MDPs.
CoRR, 2022

Rate-Optimal Online Convex Optimization in Adaptive Linear Control.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Online Linear Control with Stochastic Convex Costs and Unknown Dynamics.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Building a Clinically-Focused Problem List From Medical Notes.
Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis, 2022

2021
Minimax Regret for Stochastic Shortest Path.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Asynchronous Stochastic Optimization Robust to Arbitrary Delays.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning and Evaluating a Differentially Private Pre-trained Language Model.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Online Markov Decision Processes with Aggregate Bandit Feedback.
Proceedings of the Conference on Learning Theory, 2021

2020
Unknown mixing times in apprenticeship and reinforcement learning.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently.
Proceedings of the 37th International Conference on Machine Learning, 2020

Near-optimal Regret Bounds for Stochastic Shortest Path.
Proceedings of the 37th International Conference on Machine Learning, 2020

Apprenticeship Learning via Frank-Wolfe.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Average reward reinforcement learning with unknown mixing times.
CoRR, 2019

Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret.
CoRR, 2019

Learning and Generalization for Matching Problems.
CoRR, 2019

Learning to Screen.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Linear-Quadratic Regulators Efficiently with only √T Regret.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Incentivizing the Dynamic Workforce: Learning Contracts in the Gig-Economy.
CoRR, 2018

Planning and Learning with Stochastic Action Sets.
CoRR, 2018

Planning and Learning with Stochastic Action Sets.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Online Linear Quadratic Control.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Online Learning with Many Experts.
CoRR, 2017

Tight Bounds for Bandit Combinatorial Optimization.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Online Learning with Feedback Graphs Without the Graphs.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Following the Perturbed Leader for Online Structured Learning.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2013
Faster Optimal Planning with Partial-Order Pruning.
Proceedings of the Twenty-Third International Conference on Automated Planning and Scheduling, 2013


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