In Conferences:
- 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). [arXiv]
- 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). [arXiv]
- 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, 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). [arXiv]
- 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]
- 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])
- Regression Equilibrium.
Omer Ben-Porat and Moshe Tennenholtz.
The Twentieth ACM Conference on Economics and Computation (EC 19). [Slides, arXiv, video]
- 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)
- 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.
Journals:
- 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)
- Multi-Unit Facility Location Games.
Omer Ben-Porat and Moshe Tennenholtz.
Mathematics of Operations Research, 2019. [arXiv] (Extends and subsumes the WINE 16 paper.)
In Workshops and Symposia
- Privacy, Altruism, and Experience: Estimating the Perceived Value of Internet Data for Medical Uses.
Gilie Gefen, Omer Ben-Porat, Moshe Tennenholtz, Elad Yom-Tov.
The Web Conference 2020 Workshop on Innovative Ideas in Data Science. [arXiv][Slides] (Also presented at the AAAI 2020 Workshop on Privacy-Preserving Artificial Intelligence, PPAI 2020)
- 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)