Publications

Personalized Reinforcement Learning with a Budget of Policies.

Dmitry Ivanov and Omer Ben-Porat.

The Thirty-Eighth Annual AAAI Conference on Artificial Intelligence (AAAI 2024).

Principal-Agent Reward Shaping in MDPs.

Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler.

The Thirty-Eighth Annual AAAI Conference on Artificial Intelligence (AAAI 2024).

Learning with Exposure Constraints in Recommendation Systems.

Omer Ben-Porat and Rotem Torkan.

The Web Conference 2023  (WWW 23). [arXiv]

Frustratingly Easy Truth Discovery.

Reshef Meir, Ofra Amir, Omer Ben-Porat, Tsviel Ben Shabat, Gal Cohensius, and Lirong Xia.

The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 23). [arXiv]

Modeling Attrition in Recommender Systems with Departing Bandits.

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

The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 22).

Corporate Social Responsibility via Multi-Armed Bandits.

Tom Ron*, Omer Ben-Porat*, and Uri Shalit.

The Fourth Annual ACM Conference on Fairness, Accountability, and Transparency (ACM FACCT 2021). 

Protecting the Protected Group: Circumventing Harmful Fairness.

Omer Ben-Porat, Fedor Sandomirskiy, and Moshe Tennenholtz.

The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 21). [arXiv]

Content Provider Dynamics and Coordination in Recommendation Ecosystems.

Omer Ben-Porat, Itay Rosenberg, and Moshe Tennenholtz

Neural Information Processing Systems (NIPS) 2020.

Fiduciary Bandits.

Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, and Moshe Tennenholtz. 

The Thirty-seventh International Conference on Machine Learning (ICML 2020). [arXiv]

(A preliminary version presented at the "Young" Workshop on Economics and Computation (YoungEC) 19 [Slides, Video])

Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. 

Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard Zemel, and Craig Boutilier

The Thirty-seventh International Conference on Machine Learning (ICML 2020).

Predicting Strategic Behavior from Free Text.

Omer Ben-Porat, Sharon Hirsch, Lital Kuchy, Guy Elad, Roi Reichart, and Moshe Tennenholtz.

Journal of Artificial Intelligence Research (JAIR), 2020. [arXiv]

(Extended abstract was invited to the journal track of IJCAI 2020)

Privacy, Altruism, and Experience: Estimating the Perceived Value of Internet Data for Medical Uses.

Gilie Gefen, Omer Ben-Porat, Moshe Tennenholtz, and Elad Yom-Tov.

The Web Conference 2020 Workshop on Innovative Ideas in Data Science. [arXiv][Slides]

(A preliminary version presented at the AAAI 2020 Workshop on Privacy-Preserving Artificial Intelligence, PPAI 2020)

Regression Equilibrium.

Omer Ben-Porat and Moshe Tennenholtz.

The Twentieth ACM Conference on Economics and Computation (EC 19). [Slides, arXiv, video]

Multi-Unit Facility Location Games.

Omer Ben-Porat and Moshe Tennenholtz.

Mathematics of Operations Research. [arXiv]

(Extends and subsumes the WINE 16 paper.)

From Recommendation Systems to Facility Location Games.

Omer Ben-Porat, Gregory Goren, Itay Rosenberg, and Moshe Tennenholtz

The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 19). [Slides]

Convergence of Learning Dynamics in Information Retrieval Games.

Omer Ben-Porat, Itay Rosenberg, and Moshe Tennenholtz

The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 19).

A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers.

Omer Ben-Porat and Moshe Tennenholtz.

Neural Information Processing Systems (NIPS) 2018. [arXiv]

(A preliminary version presented at the workshop on Game-Theoretic Mechanisms for Data and Information, ICML 2018)

Efficient Crowdsourcing via Proxy Voting.

Gal Cohensius, Omer Ben-Porat, Reshef Meir, and Ofra Amir. 

The International Workshop on Computational Social Choice (COMSOC) 2018.

(Also presented at the AI^3 workshop of IJCAI 2018)

Shapley Facility Location Games.

Omer Ben-Porat and Moshe Tennenholtz. 

International Conference on Web and Internet Economics (WINE) 2017. [arXiv]

Best Response Regression.

Omer Ben-Porat and Moshe Tennenholtz.

Neural Information Processing Systems (NIPS) 2017.

Multi-Unit Facility Location Games.

Omer Ben-Porat and Moshe Tennenholtz.

International Conference on Web and Internet Economics (WINE) 2016.

Preprints

Learning under Invariable Bayesian Safety.

Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, and Moshe Tennenholtz.