Publications and Notes
Publications
- Generative Adversarial Inverse Multiagent Learning.
Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh.
To appear in proceedings of the International Conference on Learning Representations (ICLR'24).
Spotlight Talk ICLR'24 - Banzhaf Power in Hierarchical Games.
John Randolph, Denizalp Goktas, Amy Greenwald.
To appear in the proceeding of the International Conference on Autonomous Agents and Multi-Agent Systems 2024 (AAMAS'24). - Generative Adversarial Equilibrium Solvers.
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti.
To appear in proceedings of the Conference on Learning Representation (ICLR'24).
Invited talk at the Equilibrium Computation Workshop at Economics and Computation 2023 (EC'23). - Convex-Concave Zero-Sum Stochastic Stackelberg Games.
Denizalp Goktas, Arjun Prakash, Amy Greenwald.
Appeared in the Northeastern Robotics Colloquium (NERC'23)
Proceedings of the Conference on Neural Information Processing Systems (NeurIPS'23). - Tâtonnement in Homothetic Fisher Markets.
Denizalp Goktas, Sadie Zhao, and Amy Greenwald.
Proceedings of the 24th ACM Conference on Economics and Computation (EC'23). - Fisher Markets with Social Influence.
Sadie Zhao, Denizalp Goktas, Amy Greenwald.
Proceedings of the Conference of the Association for the Advancement of Artificial Intelligence (AAAI'23). - Exploitability Minimization in Games and Beyond.
Denizalp Goktas, Amy Greenwald.
Proceedings of the Conference on Neural Information Processing Systems (NeurIPS'22). - Zero-Sum Stochastic Stackelberg Games.
Denizalp Goktas, Sadie Zhao, Amy Greenwald.
Appeared in the 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM'22).Appeared in the ICLR Gamification and Multiagent Solutions Workshop (ICLR'22).
Proceedings of the Conference on Neural Information Processing Systems (NeurIPS'22). - An Algorithmic Theory of Markets and their Application to Decentralized Markets.
Denizalp Goktas.
Proceedings of the Conference of the Association for the Advancement of Artificial Intelligence (AAAI'22). - Robust No-Regret Learning in Min-Max Stackelberg Games.
Denizalp Goktas, Sadie Zhao, Amy Greenwald.
Appeared in the AAAI-22 Workshop on Adversarial Machine Learning and Beyond.
Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems 2022 (AAMAS'22). - Gradient Descent Ascent in Min-Max Stackelberg Games.
Denizalp Goktas, Amy Greenwald.
Appeared in the Games, Agents, and Incentives Workshop 2022 at the International Conference on Autonomous Agents and Multi-Agent Systems 2022 (AAMAS'22). - Convex-Concave Min-Max Stackelberg Games.
Denizalp Goktas, Amy Greenwald.
Proceedings of Conference on Neural Information Processing Systems (NeurIPS'21). - A Consumer-Theoretic Characterization of Fisher Market Equilibria.
Denizalp Goktas, Enrique Areyan Viqueira, Amy Greenwald.
Contributed Poster in Twenty-Second ACM Conference on Economics and Computation (EC’21), Proceedings of the Conference on Web and Internet Economics (WINE’21). - BoLT: Building on Local Trust to Solve Lending Market Failure.
Seth Goldstein, Denizalp Goktas, Miles Conn, Shanmukha Phani Teja Pitchuka, Mohammed Sameer, Maya Shah, Hefei Tu, Colin Swett, Shrinath Viswanathan, Jessica Xiao.
Appeared in Mechanism Design for Social Good (MD4SG'20)Additional information on project here!
Notes
Throughout my time doing research I often struggled finding resources that connected recent advances in microeconomics, optimization, mathematics and computer science that were relevant to my field. As a result, to make sense of everything I was reading, I decided to come up with a set of notes for some of the most relevant topics. I hope they can be of help for anyone looking to get introduced to the field!
Topic Surveys
Introducion to Markets for Computer Scientists
Convex Analysis and Optimization for Econ-CS
Online Learning and Online Convex Optimization (Notes compiled together with Sadie Zhao)
Miscelaneous Notes
Walrassian Equilibria in Indivisible and Divisible Settings: Linear and Convex Programming Duality
Fair Divsion, Wagering and their Equivalence
Parimutuel Betting and Fisher Markets
Disclaimer: Some of these notes are not entirely finished or have been edited more than others. I am sharing them even if not complete since they definitely could help those entering the field.
Request for feedback: I always appreciate feedback and corrections from readers.