| 2022 | COLT | Efficient decentralized multi-agent learning in asymmetric queuing systems. | Daniel Freund, Thodoris Lykouris, Wentao Weng |
| 2021 | COLT | Corruption-robust exploration in episodic reinforcement learning. | Thodoris Lykouris, Max Simchowitz, Alex Slivkins, Wen Sun |
| 2021 | STOC | Contextual search in the presence of irrational agents. | Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, Robert E. Schapire |
| 2020 | ALT | Feedback graph regret bounds for Thompson Sampling and UCB. | Thodoris Lykouris, va Tardos, Drishti Wali |
| 2020 | ICML | Bandits with Adversarial Scaling. | Thodoris Lykouris, Vahab S. Mirrokni, Renato Paes Leme |
| 2018 | COLT | Small-loss bounds for online learning with partial information. | Thodoris Lykouris, Karthik Sridharan, va Tardos |
| 2018 | ICML | Competitive Caching with Machine Learned Advice. | Thodoris Lykouris, Sergei Vassilvitskii |
| 2018 | STOC | Stochastic bandits robust to adversarial corruptions. | Thodoris Lykouris, Vahab S. Mirrokni, Renato Paes Leme |
| 2016 | SODA | Learning and Efficiency in Games with Dynamic Population. | Thodoris Lykouris, Vasilis Syrgkanis, va Tardos |
| 2014 | SAGT | Influence Maximization in Switching-Selection Threshold Models. | Dimitris Fotakis, Thodoris Lykouris, Evangelos Markakis, Svetlana Obraztsova |