Thodoris Lykouris - MIT Personal Faculty

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"Efficient Decentralized Multi-agent Learning in Asymmetric Bipartite Queueing Systems."
Daniel Freund, Thodoris Lykouris, and Wentao Weng.
Operations Research. Forthcoming.
Extended abstract appeared at COLT '22.
Journal version.
Finalist in the Applied Probability Society Student Paper Competition (2022).
“Static Pricing for Multi-unit Prophet Inequalities.”
Shuchi Chawla, Nikhil Devanur, and Thodoris Lykouris.
Operations Research. Forthcoming.
Extended abstract appeared at WINE '21.
Journal version.
"Corruption-robust Exploration in Episodic Reinforcement Learning."
Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
Mathematics of Operations Research. Forthcoming.
Extended abstract appeared at COLT '21.
Video.
"Contextual Search in the Presence of Adversarial Corruptions."
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, and Robert Schapire.
Operations Research. Vol. 71, No. 4 (2023): 1120-1135.
Extended abstract appeared at STOC '21.
Video.
Journal version.
"Competitive Caching with Machine Learned Advice."
Thodoris Lykouris and Sergei Vassilvitskii.
Journal of the ACM. Vol. 68, No. 4, Art. 24 (2021): 1-25.
Extended abstract appeared at ICML '18.
Video.
Journal version.
"Small-loss Bounds for Online Learning with Partial Information."
Thodoris Lykouris, Karthik Sridharan, and Éva Tardos.
Mathematics of Operations Research. Vol. 47, No. 3 (2022): 2186-2218
Extended abstract appeared at COLT '18.
Video.
Journal version.
Finalist in the INFORMS Nicholson Student Paper Competition (2018).
"Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework."
Siddhartha Banerjee, Daniel Freund, and Thodoris Lykouris.
Operations Research. Vol. 70, No. 3 (2022): 1783-1805.
Extended abstract appeared at EC '17.
Video.
Journal version.
Finalist in the Applied Probability Society Student Paper Competition (2017).

"Learning to Defer in Content Moderation: The Human-AI Interplay."
Thodoris Lykouris and Wentao Weng.
"Quantifying the Cost of Learning in Queueing Systems."
Daniel Freund, Thodoris Lykouris, and Wentao Weng.
Extended abstract to appear at NeurIPS '23.
"Group Fairness in Dynamic Refugee Assignment."
Daniel Freund, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt, and Wentao Weng.
Extended abstract appeared at EC '23 and at the non-archival track of FORC'23.
"Learning in Stackelberg Games with Non-myopic Agents"
Nika Haghtalab, Thodoris Lykouris, Sloan Nietert, and Alexander Wei.
Extended abstract appeared at EC '22
“Stochastic Bandits Robust to Adversarial Corruptions.”
Thodoris Lykouris, Vahab Mirrokni, and Renato Paes Leme.
Extended abstract appeared at STOC '18.
Video.
“Learning and Efficiency in Games with Dynamic Population.”
Thodoris Lykouris, Vasilis Syrgkanis, and Éva Tardos.
Extended abstract appeared at SODA '16.

"Quantifying the Cost of Learning in Queueing Systems."
Daniel Freund, Thodoris Lykouris, and Wentao Weng.
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023).
"Group Fairness in Dynamic Refugee Assignment"
Daniel Freund, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt and Wentao Weng.
24th ACM Conference on Economics and Computation (EC 2023).
Journal version: Under review.
"Efficient Decentralized Multi-agent Learning in Asymmetric Queuing Systems."
Daniel Freund, Thodoris Lykouris, and Wentao Weng.
35th Annual Conference on Learning Theory (COLT 2022).
Journal version: Operations Research.
"Learning in Stackelberg Games with Non-myopic Agents"
Nika Haghtalab, Thodoris Lykouris, Sloan Nietert, and Alexander Wei.
23rd ACM Conference on Economics and Computation (EC 2022).
Journal version: Under review.
"Contextual Search in the Presence of Irrational Agents."
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, and Robert Schapire.
53rd Annual ACM Symposium on the Theory of Computing (STOC 2021).
Journal version: Operations Research.
"Corruption-robust Exploration in Episodic Reinforcement Learning."
Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
34th Annual Conference on Learning Theory (COLT 2021).
Journal version: Under review.
"Static Pricing for Multi-unit Prophet Inequalities"
Thodoris Lykouris, Shuchi Chawla, and Nikhil Devanur
17th Conference on Web and Internet Economics (WINE 2021).
Journal version: Operations Research.
"Constrained Episodic Reinforcement Learning in Concave-convex and Knapsack Settings."
Kianté Brantley, Miroslav Dudik, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun.
34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020).
"Bandits with Adversarial Scaling."
Thodoris Lykouris, Vahab Mirrokni, and Renato Paes Leme.
37th International Conference on Machine Learning (ICML 2020).
Video.
"Feedback Graph Regret Bounds for Thompson Sampling and UCB."
Thodoris Lykouris, Éva Tardos, and Drishti Wali.
31st International Conference on Algorithmic Learning Theory (ALT 2020).
"Advancing Subgroup Fairness via Sleeping Experts."
Avrim Blum and Thodoris Lykouris.
11th Innovations in Theoretical Computer Science Conference (ITCS 2020).
"On Preserving Non-discrimination when Combining Expert Advice."
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, and Nathan Srebro.
32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018).
"Competitive Caching with Machine Learned Advice."
Thodoris Lykouris and Sergei Vassilvitskii.
35th International Conference on Machine Learning (ICML 2018).
Journal version: Journal of the ACM.
"Stochastic Bandits Robust to Adversarial Corruptions."
Thodoris Lykouris, Vahab Mirrokni, and Renato Paes Leme.
50th ACM Annual Symposium on Theory of Computing (STOC 2018).
Journal version: Under preparation.
"Small-loss Bounds for Online Learning with Partial Information."
Thodoris Lykouris, Karthik Sridharan, and Éva Tardos.
31st Annual Conference on Learning Theory (COLT 2018).
Journal version: Mathematics of Operations Research.
"Pricing and Optimization in Shared Vehicle Systems: An Approximation Framework."
Siddhartha Banerjee, Daniel Freund, and Thodoris Lykouris.
18th ACM Conference on Economics and Computation (EC 2017).
Journal version: Operations Research.
"Learning in Games: Robustness of Fast Convergence."
Dylan Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, and Éva Tardos.
30th Annual Conference on Neural Information Processing Systems (NeurIPS 2016).
Video.
"Learning and Efficiency in Games with Dynamic Population."
Thodoris Lykouris, Vasilis Syrgkanis, and Éva Tardos.
27th ACM-SIAM Symposium on Discrete Algorithms (SODA 2016).
Journal version: Under preparation.
"Influence Maximization in Switching-selection Threshold Models."
Dimitris Fotakis, Thodoris Lykouris, Evangelos Markakis, and Svetlana Obraztsova.
7th International Symposium on Algorithmic Game Theory (SAGT 2014).