Alexander Peysakhovich

According to our database, Alexander Peysakhovich authored at least 38 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Attention Sorting Combats Recency Bias In Long Context Language Models.

Alexander Peysakhovich, Adam Lerer

CoRR, 2023

Diagnosis Uncertain Models For Medical Risk Prediction.

Alexander Peysakhovich, Rich Caruana, Yin Aphinyanaphongs

CoRR, 2023

Implementing Fairness Constraints in Markets Using Taxes and Subsidies.

Alexander Peysakhovich, Christian Kroer, Nicolas Usunier

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Computing Large Market Equilibria Using Abstractions.

Christian Kroer, Alexander Peysakhovich, Eric Sodomka, Nicolás E. Stier Moses

Oper. Res., 2022

Parity in Markets - Methods, Costs, and Consequences.

Alexander Peysakhovich, Christian Kroer, Nicolas Usunier

CoRR, 2022

Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes.

Leon Yao, Caroline Lo, Israel Nir, Sarah Tan, Ariel Evnine, Adam Lerer, Alex Peysakhovich

CoRR, 2022

2021

An Attract-Repel Decomposition of Undirected Networks.

Alexander Peysakhovich, Léon Bottou

CoRR, 2021

Online Market Equilibrium with Application to Fair Division.

Yuan Gao, Alex Peysakhovich, Christian Kroer

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions.

Tom Yan, Christian Kroer, Alexander Peysakhovich

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian.

Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alexander Peysakhovich, Aldo Pacchiano, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

"Other-Play" for Zero-Shot Coordination.

Hengyuan Hu, Adam Lerer, Alex Peysakhovich, Jakob N. Foerster

Proceedings of the 37th International Conference on Machine Learning, 2020

Robust Market Equilibria with Uncertain Preferences.

Riley Murray, Christian Kroer, Alex Peysakhovich, Parikshit Shah

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

The Good, the Bad, and the Unflinchingly Selfish: Pro-sociality can be Well Predicted Using Payoffs and Three Behavioral Types.

Ziv Epstein, Alexander Peysakhovich, David G. Rand

ACM Trans. Economics and Comput., 2019

Scalable Fair Division for 'At Most One' Preferences.

Christian Kroer, Alexander Peysakhovich

CoRR, 2019

Fair Division Without Disparate Impact.

Alexander Peysakhovich, Christian Kroer

CoRR, 2019

Robust Multi-agent Counterfactual Prediction.

Alexander Peysakhovich, Christian Kroer, Adam Lerer

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

Pytorch-BigGraph: A Large Scale Graph Embedding System.

Adam Lerer, Ledell Wu, Jiajun Shen, Timothée Lacroix, Luca Wehrstedt, Abhijit Bose, Alex Peysakhovich

Proceedings of Machine Learning and Systems 2019, 2019

Discovering Context Effects from Raw Choice Data.

Arjun Seshadri, Alex Peysakhovich, Johan Ugander

Proceedings of the 36th International Conference on Machine Learning, 2019

Observational Data for Heterogeneous Treatment Effects with Application to Recommender Systems.

Akos Lada, Alexander Peysakhovich, Diego Aparicio, Michael Bailey

Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

Reinforcement Learning and Inverse Reinforcement Learning with System 1 and System 2.

Alexander Peysakhovich

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Learning Existing Social Conventions via Observationally Augmented Self-Play.

Adam Lerer, Alexander Peysakhovich

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Improving pairwise comparison models using Empirical Bayes shrinkage.

Stephen Ragain, Alexander Peysakhovich, Johan Ugander

CoRR, 2018

Backplay: "Man muss immer umkehren".

Cinjon Resnick, Roberta Raileanu, Sanyam Kapoor, Alex Peysakhovich, Kyunghyun Cho, Joan Bruna

CoRR, 2018

Learning Social Conventions in Markov Games.

Adam Lerer, Alexander Peysakhovich

CoRR, 2018

Learning Causal Effects From Many Randomized Experiments Using Regularized Instrumental Variables.

Alexander Peysakhovich, Dean Eckles

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Consequentialist conditional cooperation in social dilemmas with imperfect information.

Alexander Peysakhovich, Adam Lerer

Proceedings of the 6th International Conference on Learning Representations, 2018

Prosocial Learning Agents Solve Generalized Stag Hunts Better than Selfish Ones.

Alexander Peysakhovich, Adam Lerer

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Towards AI that Can Solve Social Dilemmas.

Alexander Peysakhovich, Adam Lerer

Proceedings of the 2018 AAAI Spring Symposia, 2018

Consequentialist Conditional Cooperation in Social Dilemmas with Imperfect Information (Short Workshop Version).

Alexander Peysakhovich, Adam Lerer

Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Maintaining cooperation in complex social dilemmas using deep reinforcement learning.

Adam Lerer, Alexander Peysakhovich

CoRR, 2017

Learning context-dependent preferences from raw data.

Alexander Peysakhovich, Johan Ugander

Proceedings of the 12th workshop on the Economics of Networks, Systems and Computation, 2017

Multi-Agent Cooperation and the Emergence of (Natural) Language.

Angeliki Lazaridou, Alexander Peysakhovich, Marco Baroni

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Recency, Records, and Recaps: Learning and Nonequilibrium Behavior in a Simple Decision Problem.

Drew Fudenberg, Alexander Peysakhovich

ACM Trans. Economics and Comput., 2016

Habits of Virtue: Creating Norms of Cooperation and Defection in the Laboratory.

Alexander Peysakhovich, David G. Rand

Manag. Sci., 2016

Asymmetric Effects of Favorable and Unfavorable Information on Decision Making Under Ambiguity.

Alexander Peysakhovich, Uma R. Karmarkar

Manag. Sci., 2016

Combining observational and experimental data to find heterogeneous treatment effects.

Alexander Peysakhovich, Akos Lada

CoRR, 2016

The Good, the Bad, and the Unflinchingly Selfish: Cooperative Decision-Making can be Predicted with high Accuracy when using only Three Behavioral Types.

Ziv Epstein, Alexander Peysakhovich, David G. Rand

Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

2014

Recency, records and recaps: learning and non-equilibrium behavior in a simple decision problem.

Drew Fudenberg, Alexander Peysakhovich

Proceedings of the ACM Conference on Economics and Computation, 2014