Journal Articles
- "Efficient Decentralized Multi-agent Learning in Asymmetric Bipartite Queueing Systems."
with Daniel Freund and Wentao Weng.
Operations Research. Vol. 72, No. 3 (2024): 1049-1070.
Conference version: 35th Annual Conference on Learning Theory (COLT 2022).
Journal version
Video of a 60-minute talk that Daniel gave in the SNAPP seminar series in April 2023.
Finalist in the Applied Probability Society Student Paper Competition (2022). - "Learning in Stackelberg Games with Non-myopic Agents"
with Nika Haghtalab,, Sloan Nietert, and Alexander Wei.
Operations Research. Forthcoming (2025).
Conference version: 23rd ACM Conference on Economics and Computation (EC 2022). - “Static Pricing for Multi-unit Prophet Inequalities.”
with Shuchi Chawla and Nikhil Devanur.
Operations Research. Vol. 72, No. 4 (2024): 1388-1399.
Conference version: 17th Conference on Web and Internet Economics (WINE 2021).
Journal version. - "Corruption-robust Exploration in Episodic Reinforcement Learning."
with Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
Mathematics of Operations Research. Vol. 50, No. 2 (2024): 1277-1304.
Conference version: 34th Annual Conference on Learnint Theory (COLT 2021).
Journal version.
Video of a 60-minute talk that I gave in the RL Theory seminar series in November 2020. - "Contextual Search in the Presence of Adversarial Corruptions."
with Akshay Krishnamurthy, Chara Podimata, and Robert Schapire.
Operations Research. Vol. 71, No. 4 (2023): 1120-1135.
Conference version: 53rd ACM Symposium on Theory of Computing (STOC 2021).
Journal version.
Video of a 45-minute talk that Chara gave at the Simons Institute in September 2022. - "Competitive Caching with Machine Learned Advice."
with Sergei Vassilvitskii.
Journal of the ACM. Vol. 68, No. 4, Art. 24 (2021): 1-25.
Conference version: 35th International Conference on Machine Learning (ICML 2018).
Journal version. - "Small-loss Bounds for Online Learning with Partial Information."
with Karthik Sridharan and Éva Tardos.
Mathematics of Operations Research. Vol. 47, No. 3 (2022): 2186-2218.
Conference version: 31st Annual Conference on Learning Theory (2018).
Journal version.
Video of a 10-minute talk that I gave at the COLT 2018 conference in July 2018.
Finalist in the INFORMS Nicholson Student Paper Competition (2018). - "Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework."
with Siddhartha Banerjee and Daniel Freund.
Operations Research. Vol. 70, No. 3 (2022): 1783-1805.
Conference version: 18th ACM Conference on Economics and Computation (EC 2017).
Journal version.
Video of a 20-minute talk that I gave at the EC 2017 conference in June 2017.
Finalist in the Applied Probability Society Student Paper Competition (2017).
Working Papers
- "Scheduling with Uncertain Holding Costs and its Application to Content Moderation."
with Caner Gocmen, Deeksha Sinha, and Wentao Weng.
Major Revision at Management Science. - "Learning to Defer in Congested Systems: The AI-Human Interplay."
with Wentao Weng.
Under second-round review at Operations Research (after Major Revision).
Video of a 60-minute talk that I gave in the SNAPP seminar series in May 2024.
Finalist in the Junior Faculty Interest Group Paper Competition (2024). - "Social Learning with Limited Attention: Negative Reviews Persist under Newest First."
with Jackie Baek and Atanas Dinev.
Under second-round review at Operations Research (after Major Revision).
Conference version: 25th ACM Conference on Economics and Computation (EC 2024).
Accepted for presentation in the 2025 MSOM SIG (Service Science).
Finalist in the Junior Faculty Interest Group Paper Competition (2025). - "The Transient Cost of Learning in Queueing Systems."
with Daniel Freund and Wentao Weng.
Under second-round review at Operations Research (after Reject-and-Resubmit).
Conference version: 37th Conference on Neural Information Processing Systems (NeurIPS 2023). - "Group Fairness in Dynamic Refugee Assignment."
with Daniel Freund, Elisabeth Paulson, Bradley Sturt, and Wentao Weng.
Major Revision at Operations Research.
Conference version: 24th ACM Conference on Economics and Computation (EC 2023).
Video of a 60-minute talk that Daniel gave at the TOC4Fairness in February 2024.
Video of a 18-minute talk that Wentao gave at the EC 2023 conference in June 2023. - “Stochastic Bandits Robust to Adversarial Corruptions.”
with Vahab Mirrokni and Renato Paes Leme.
Conference version: 50th ACM Symposium on Theory of Computing (STOC 2018).
Video of a 75-minute bootcamp talk that I gave at the Simons Institute in August 2022.
Video of a 20-minute talk that I gave at the STOC 2018 conference in June 2018. - “Learning and Efficiency in Games with Dynamic Population.”
with Vasilis Syrgkanis, and Éva Tardos.
Major Revision at Mathematics of Operations Research.
Conference version: 27th ACM-SIAM Symposium on Discrete Algorithms (SODA 2016).
Video of a 45-minute talk that Éva gave at the Simons Institute in March 2018.
Conference Publications Not Listed Above
- "Bayesian Decision-Making under Misspecified Priors with Applications to Meta-Learning."
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert Schapire (contributional author order).
35th Annual Conference on Neural Information Processing Systems (NeurIPS 2021). - "Constrained Episodic Reinforcement Learning in Concave-convex and Knapsack Settings."
with Kianté Brantley, Miroslav Dudík, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020). - "Bandits with Adversarial Scaling."
with Vahab Mirrokni and Renato Paes Leme.
37th International Conference on Machine Learning (ICML 2020).
Video of a 15-minute talk that I gave at the ICML 2020 conference in July 2020. - "Feedback Graph Regret Bounds for Thompson Sampling and UCB."
with Éva Tardos and Drishti Wali.
31st International Conference on Algorithmic Learning Theory (ALT 2020). - "Advancing Subgroup Fairness via Sleeping Experts."
with Avrim Blum.
11th Innovations in Theoretical Computer Science Conference (ITCS 2020). - "On Preserving Non-discrimination when Combining Expert Advice."
with Avrim Blum, Suriya Gunasekar, and Nathan Srebro.
32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018). - "Learning in Games: Robustness of Fast Convergence."
with Dylan Foster, Zhiyuan Li, Karthik Sridharan, and Éva Tardos.
30th Annual Conference on Neural Information Processing Systems (NeurIPS 2016).
Video of a 30-minute talk that I gave at the YoungEC 2017 workshop in January 2017. - "Influence Maximization in Switching-selection Threshold Models."
with Dimitris Fotakis, Evangelos Markakis, and Svetlana Obraztsova.
7th International Symposium on Algorithmic Game Theory (SAGT 2014).
PhD Dissertation
- "Effective Online Decision-making in Complex Multi-agent Systems."
Thodoris Lykouris.
PhD diss., Cornell University, 2019.
Finalist for the George B. Dantzig Dissertation Award (2020).