Orin Levy

About

I am a PhD student in the School of Computer Science at Tel Aviv University (TAU), where I am fortunate to have Prof. Yishay Mansour as my advisor.  Prior to that, I received my BSc in Computer Science from Tel Aviv University. 

I am broadly interested in theory and applications of Machine Learning. Currently, my research is focused on theory of Reinforcement Learning and Online Learning. 

Email: orinlevy AT mail.tau.ac.il

Google Scholar

News

• New paper was accepted to NeurIPS 2024!

• Two papers were accepted to EWRL 2024!

• Our paper "Eluder-based Regret for Stochastic Contextual MDPs"  was accepted to ICML 2024!

• Our paper " Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation"  was accepted to ICML 2023!

• Our paper "Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP" was accepted to AAAI 2023 (Oral presentation) ! 

Papers

• Batch Ensemble for Variance Dependent Regret in Stochastic Bandits

Asaf Cassel, Orin Levy, Yishay Mansour

AAAI 2025

[ArXiv]

• Online Weighted Paging with Unknown Weights

Orin Levy, Noam Touitou, Aviv Rosenberg

NeurIPS 2024

[ArXiv]

• Regret Guarantees for Adversarial Contextual Bandits with Delayed Feedback

Orin Levy, Liad Erez, Yishay Mansour

EWRL 2024

[Workshop Paper]

• Eluder-based Regret for Stochastic Contextual MDPs

Orin Levy, Asaf Cassel, Alon Cohen, Yishay Mansour

ICML 2024

[ArXiv]

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

Orin Levy, Alon Cohen, Asaf Cassel, Yishay Mansour

ICML 2023, EWRL 2024

[ArXiv]

• Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP

Orin Levy and Yishay Mansour

AAAI 2023 (Oral), EWRL 2022, ICML 2022 workshop on CFOL

[ArXiv]

• Learning Efficiently Function Approximation for Contextual MDP

Orin Levy and Yishay Mansour

EWRL 2022

[ArXiv]

Teaching

• Spring 24/25: Reinforcement Learning (Teaching Assistant)

• Fall 24/25: Introduction to Machine Learning (Teaching Assistant)

• Spring 23/24: Reinforcement Learning (Teaching Assistant)

• Fall 23/24: Introduction to Machine Learning (Teaching Assistant)

• Spring 22/23: Introduction to Machine Learning (Teaching Assistant)

• Fall 22/23: Introduction to Machine Learning (Teaching Assistant)

• Fall 21/22: Advanced Topics in ML and AGT (Graduate level course, grader)

• Spring 20/21: Reinforcement Learning (Grader)