Publications and Notes
Denizalp Goktas (2022), “An Algorithmic Theory of Markets and their Application to Decentralized Markiets”, Forthcoming AAAI'22 Doctoral Consortium.
Denizalp Goktas, Sadie Zhao and Amy Greenwald (2021). “Robust No-Regret Learning in Min-Max Stackelberg Games”, The AAAI-22 Workshop on Adversarial Machine Learning and Beyond.
Denizalp Goktas and Amy Greenwald (2021). “Gradient Descent Ascent in Min-Max Stackelberg Games”. In Submission.
Denizalp Goktas, Enrique Areyan Viqueira, and Amy Greenwald (2021). “Tâtonnement Beyond Constant Elasticity of Substitution”. In: Twenty-Second ACM Conference on Economics and Computation (EC’21) - Contributed Poster, Forthcoming in Conference on Web and Internet Economics (WINE’22).
Goldstein, S., Goktas, D., Conn, M., Pitchuka, S., Sameer, M., Shah, M., Swett, C., Tu, H., Viswanathan, S., & Xiao. (2020). “BoLT: Building on Local Trust to Solve Lending Market Failure”. In: Mechanism Design for Social Good - Additional information on project here!
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!
Online Learning and Online Convex Optimization (Notes compiled together with Sadie Zhao)
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.