Chara Podimata

Research

Preprints

Bandits with Deterministically Evolving Preference Effects
Khashayar Khosravi, Renato Paes Leme, Chara Podimata, and Apostolis Tsorvantzis

Recommending to Strategic Users
Andreas Haupt, Dylan Hadfield-Menell, and Chara Podimata

Strategyproof Decision-Making in Panel Data Settings and Beyond
Keegan Harris, Anish Agarwal, Chara Podimata, and Zhiwei Steven Wu

Journal Publications

Contextual Search in the Presence of Adversarial Corruptions
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, and Robert Schapire

Operations Research, 2022

(OR22)

Conference Publications

2023

Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
Nika Haghtalab, Chara Podimata, and Kunhe Yang

In Proc. of the 37th conference on Neural Information Processing Systems

(NeurIPS23)

Spotlight

Strategic Apple Tasting
Keegan Harris, Chara Podimata, and Zhiwei Steven Wu

In Proc. of the 37th conference on Neural Information Processing Systems

(NeurIPS23)

2022

Corruption-Robust Contextual Search through Density Updates
Renato Paes Leme, Chara Podimata, and Jon Schneider

In Proc. of the 35th Annual Conference on Learning Theory

(COLT22)

Information Discrepancy in Strategic Learning
Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu, and Juba Ziani

In Proc. of the 39th International Conference on Machine Learning

(ICML22)

2021

Adaptive Discretization for Adversarial Lipschitz Bandits
Chara Podimata and Alex Slivkins

In Proc. of the 34th Annual Conference on Learning Theory

(COLT21)

Contextual Search in the Presence of Irrational Agents
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, and Robert Schapire

In Proc. of the 53rd ACM Symposium on Theory of Computing

(STOC21)

2020

Learning Strategy-Aware Linear Classifiers
Yiling Chen, Yang Liu, and Chara Podimata
In Proc. of the 34th Conference on Neural Information Processing Systems (NeurIPS20)

No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David M. Pennock, Chara Podimata and Jennifer Wortman Vaughan
In Proc. of the 37th International Conference on Machine Learning (ICML20)

2019

A Bridge Βetween Liquid and Social Welfare in Combinatorial Auctions with Submodular Bidders
Dimitris Fotakis, Kyriakos Lotidis and Chara Podimata
In Proc. of the 33rd AAAI Conference on Artificial Intelligence (AAAI19)

2018

Strategyproof Linear Regression in High Dimensions
Yiling Chen, Chara Podimata, Ariel D. Procaccia and Nisarg Shah.
In Proc. of the 19th ACM Conference on Economics and Computation (EC18)
Among the 5 shortlisted papers for the Best Paper Award (EC18).

Learning to Bid without Knowing your Value
Zhe Feng, Chara Podimata and Vasilis Syrgkanis.
In Proc. of the 19th ACM Conference on Economics and Computation (EC18)
Spotlight award 2nd place prize at the 13th Annual ML Symposium (NYAS).
pdf github slides poster

Expository

Strategyproof Linear Regression in High Dimensions: an Overview
Yiling Chen, Chara Podimata, Ariel D. Procaccia and Nisarg Shah.
In SIGEcom Exchanges, Issue 17.1, April 2019
pdf

PhD Dissertation

Incentive-Aware Machine Learning for Decision Making
pdf