Bid optimization for broad match ad auctions, Eyal Even-Dar, Vahab S. Mirrokni, S. Muthukrishnan, Yishay Mansour, Uri Nadav, WWW, 2009, pp. 231-240.
On the Convergence of Regret Minimization Dynamics in Concave Games, Eyal Even-Dar, Yishay Mansour, Uri Nadav, 41st Annual ACM Symposium on Theory of Computing, STOC, 2009, pp. 523-532.
Online Learning with Global Cost Functions, Eyal Even-Dar, Robert Kleinberg, Shie Mannor, Yishay Mansour, 22nd Annual Conference on Learning Theory, COLT, 2009.
Online Markov Decision Processes, Eyal Even-Dar, Sham. M. Kakade, Yishay Mansour, Math. Oper. Res., vol. 34 (2009), pp. 726-736.
Position Auctions with Bidder-Specific Minimum Prices, Eyal Even-Dar, Jon Feldman, Yishay Mansour, S. Muthukrishnan, Fourth Workshop on Ad Auctions; Workshop on Internet and Network Economics (WINE), 2008.
Theory research at Google, Gagan Aggarwal, Nir Ailon, Florin Constantin, Eyal Even-Dar, Jon Feldman, Gereon Frahling, Monika R. Henzinger, S. Muthukrishnan, Noam Nisan, Martin Pál, Mark Sandler, Anastasios Sidiropoulos, SIGACT News, vol. 39 (2008), pp. 10-28.
A Note on Maximizing the Spread of Influence in Social Networks, Eyal Even-Dar, Asaf Shapira, Internet and Network Economics (WINE), 2007, pp. 281-286.
Sponsored Search with Contexts, Eyal Even-Dar, Michael Kearns, Jennifer Wortman, Internet and Network Economics (WINE), 2007, pp. 312-317.
Tutorial summary: Convergence of natural dynamics to equilibria, Eyal Even-Dar, Vahab S. Mirrokni, ICML, 2009, pp. 173.
Regret to the best vs. regret to the average, Eyal Even-Dar, Michael Kearns, Yishay Mansour, Jennifer Wortman, Mach. Learn., vol. 72 (2008), pp. 21-37.
Convergence time to Nash equilibrium in load balancing, Eyal Even-Dar, Alex Kesselman, Yishay Mansour, ACM Trans. Algorithms, vol. 3 (2007), pp. 32.
The value of observation for monitoring dynamic systems, Eyal Even-Dar, Sham M. Kakade, Yishay Mansour, IJCAI'07: Proceedings of the 20th international joint conference on Artifical intelligence, 2007, pp. 2474-2479.
Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems, Eyal Even-Dar, Shie Mannor, Yishay Mansour, J. Mach. Learn. Res., vol. 7 (2006), pp. 1079-1105.
On nash equilibria for a network creation game, Susanne Albers, Stefan Eilts, Eyal Even-Dar, Yishay Mansour, Liam Roditty, SODA '06: Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm, 2006, pp. 89-98.
Routing without regret: on convergence to nash equilibria of regret-minimizing algorithms in routing games, Avrim Blum, Eyal Even-Dar, Katrina Ligett, PODC '06: Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing, 2006, pp. 45-52.
Fast convergence of selfish rerouting, Eyal Even-Dar, Yishay Mansour, SODA '05: Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms, 2005, pp. 772-781.
Reinforcement learning in POMDPs without resets, Eyal Even-Dar, Sham M. Kakade, Yishay Mansour, IJCAI'05: Proceedings of the 19th international joint conference on Artificial intelligence, 2005, pp. 690-695.
Learning Rates for Q-learning, Eyal Even-Dar, Yishay Mansour, J. Mach. Learn. Res., vol. 5 (2004), pp. 1-25.
PAC Bounds for Multi-armed Bandit and Markov Decision Processes, Eyal Even-Dar, Shie Mannor, Yishay Mansour, COLT '02: Proceedings of the 15th Annual Conference on Computational Learning Theory, 2002, pp. 255-270.
Learning Rates for Q-Learning, Eyal Even-Dar, Yishay Mansour, COLT '01/EuroCOLT '01: Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory, 2001, pp. 589-604.