Lee Cohen

About

I'm a postdoctoral researcher at Stanford, hosted by Omer Reingold.

Prior to that, I was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC). I completed my PhD in Computer Science at Tel Aviv University, where I was very fortunate to be advised by Yishay Mansour.

I am broadly interested in learning theory, with a particular interest in problems that relate to societal challenges.

Email: leecohencs AT gmail DOT com

Google Scholar

News

• Aug 23:  Avrim Blum and I are organizing DavidFest & YishayFest: Celebratory/milestone birthday workshops in honor of David McAllester and Yishay Mansour at TTIC! 

• 2021: Check out our WiML-T event at COLT 2021!

• Oct 2020: Interested in ML theory & Identify yourself as a woman?  You can sign up for our mentorship program for women in machine learning theory either as a mentor, mentee, or both!

• Feb-Mar 2020: Visiting Efficient Algorithms research group, TU Berlin

Papers

• Utilizing Adversarial Examples for Bias Mitigation and Accuracy Enhancement

Pushkar Shukla, Dhruv Srikanth, Lee Cohen, Matthew Turk

Preprint

[arxiv]

• Learnability Gaps of Strategic Classification

Lee Cohen,  Yishay Mansour, Shay Moran, Han Shao

Preprint

[arxiv]

• Bayesian Strategic Classification

Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

Preprint

[arxiv]

• Incentivized Collaboration in Active Learning

Lee Cohen, Han Shao

Accepted to Symposium on Foundations of Responsible Computing (FORC) 2024

[arxiv]

• Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback

Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R Walter

Conference on Neural Information Processing Systems (NeurIPS) 2023

[arxiv]

• Finding Safe Zones of Markov Decision Processes Policies

Lee Cohen,  Yishay Mansour and  Michal Moshkovitz

Conference on Neural Information Processing Systems (NeurIPS) 2023

[arxiv]

• Sequential Strategic Screening

Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

International Conference on Machine Learning (ICML) 2023

[arxiv]

• Modeling Attrition in Recommender Systems with Departing Bandits

Omer Ben-Porat*,  Lee Cohen*,  Liu Leqi*,  Zachary C. Lipton , and Yishay Mansour

Oral presentation, AAAI Conference on Artificial Intelligence (AAAI) 2022 (Oral)

[arXiv]

• Dueling Bandits with Team Comparisons

Lee Cohen*,  Ulrike Schmidt-Kraepelin* and Yishay Mansour

Conference on Neural Information Processing Systems (NeurIPS) 2021

[arxiv]

• Sample Complexity of Uniform Convergence for Multicalibration 

Eliran Shabat*,  Lee Cohen*,  and Yishay Mansour

Conference on Neural Information Processing Systems (NeurIPS) 2020 

[arxiv]

• Efficient Candidate Screening under Multiple Tests and Implications for Fairness  

Lee Cohen,  Zachary C. Lipton, and Yishay Mansour

Symposium on Foundations of Responsible Computing (FORC) 2020

[arxiv][talk]

• Optimal Algorithm for Bayesian Incentive-Compatible Exploration

Lee Cohen and Yishay Mansour

ACM Conference on Economics and Computation (EC) 2019

[arxiv][talk]

* Equal contribution. 

Teaching

• Spring 19/20: Reinforcement Learning (Teaching assistant)

• Spring 18/19: Reinforcement Learning (Teaching assistant)

• Fall 18/19: Advanced topics in ML and AGT (Graduate level course, grader)