2009 |
29 | EE | Eyal Even-Dar,
Vahab S. Mirrokni,
S. Muthukrishnan,
Yishay Mansour,
Uri Nadav:
Bid optimization for broad match ad auctions.
WWW 2009: 231-240 |
28 | EE | Eyal Even-Dar,
Yishay Mansour,
Vahab S. Mirrokni,
S. Muthukrishnan,
Uri Nadav:
Bid Optimization in Broad-Match Ad Auctions
CoRR abs/0901.3754: (2009) |
2008 |
27 | EE | Eyal Even-Dar,
Jon Feldman,
Yishay Mansour,
S. Muthukrishnan:
Position Auctions with Bidder-Specific Minimum Prices.
WINE 2008: 577-584 |
26 | EE | Eyal Even-Dar:
Reinforcement Learning.
Encyclopedia of Algorithms 2008 |
25 | EE | Eyal Even-Dar,
Michael Kearns,
Yishay Mansour,
Jennifer Wortman:
Regret to the best vs. regret to the average.
Machine Learning 72(1-2): 21-37 (2008) |
24 | EE | Gagan Aggarwal,
Nir Ailon,
Florin Constantin,
Eyal Even-Dar,
Jon Feldman,
Gereon Frahling,
Monika Rauch Henzinger,
S. Muthukrishnan,
Noam Nisan,
Martin Pál,
Mark Sandler,
Anastasios Sidiropoulos:
Theory research at Google.
SIGACT News 39(2): 10-28 (2008) |
2007 |
23 | EE | Eyal Even-Dar,
Michael J. Kearns,
Yishay Mansour,
Jennifer Wortman:
Regret to the Best vs. Regret to the Average.
COLT 2007: 233-247 |
22 | EE | Eyal Even-Dar,
Sham M. Kakade,
Yishay Mansour:
The Value of Observation for Monitoring Dynamic Systems.
IJCAI 2007: 2474-2479 |
21 | EE | Eyal Even-Dar,
Michael J. Kearns,
Siddharth Suri:
A network formation game for bipartite exchange economies.
SODA 2007: 697-706 |
20 | EE | Eyal Even-Dar,
Asaf Shapira:
A Note on Maximizing the Spread of Influence in Social Networks.
WINE 2007: 281-286 |
19 | EE | Eyal Even-Dar,
Michael J. Kearns,
Jennifer Wortman:
Sponsored Search with Contexts.
WINE 2007: 312-317 |
18 | EE | Eyal Even-Dar,
Alexander Kesselman,
Yishay Mansour:
Convergence time to Nash equilibrium in load balancing.
ACM Transactions on Algorithms 3(3): (2007) |
2006 |
17 | EE | Eyal Even-Dar,
Sham M. Kakade,
Michael S. Kearns,
Yishay Mansour:
(In)Stability properties of limit order dynamics.
ACM Conference on Electronic Commerce 2006: 120-129 |
16 | EE | Eyal Even-Dar,
Michael J. Kearns,
Jennifer Wortman:
Risk-Sensitive Online Learning.
ALT 2006: 199-213 |
15 | EE | Eyal Even-Dar,
Michael J. Kearns:
A Small World Threshold for Economic Network Formation.
NIPS 2006: 385-392 |
14 | EE | Avrim Blum,
Eyal Even-Dar,
Katrina Ligett:
Routing without regret: on convergence to nash equilibria of regret-minimizing algorithms in routing games.
PODC 2006: 45-52 |
13 | EE | Susanne Albers,
Stefan Eilts,
Eyal Even-Dar,
Yishay Mansour,
Liam Roditty:
On nash equilibria for a network creation game.
SODA 2006: 89-98 |
12 | EE | Eyal Even-Dar,
Shie Mannor,
Yishay Mansour:
Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems.
Journal of Machine Learning Research 7: 1079-1105 (2006) |
2005 |
11 | EE | Eyal Even-Dar,
Sham M. Kakade,
Yishay Mansour:
Reinforcement Learning in POMDPs Without Resets.
IJCAI 2005: 690-695 |
10 | EE | Eyal Even-Dar,
Yishay Mansour:
Fast convergence of selfish rerouting.
SODA 2005: 772-781 |
9 | EE | Eyal Even-Dar,
Sham M. Kakade,
Yishay Mansour:
Planning in POMDPs Using Multiplicity Automata.
UAI 2005: 185-192 |
2004 |
8 | EE | Eyal Even-Dar,
Sham M. Kakade,
Yishay Mansour:
Experts in a Markov Decision Process.
NIPS 2004 |
2003 |
7 | EE | Eyal Even-Dar,
Yishay Mansour:
Approximate Equivalence of Markov Decision Processes.
COLT 2003: 581-594 |
6 | EE | Eyal Even-Dar,
Alexander Kesselman,
Yishay Mansour:
Convergence Time to Nash Equilibria.
ICALP 2003: 502-513 |
5 | | Eyal Even-Dar,
Shie Mannor,
Yishay Mansour:
Action Elimination and Stopping Conditions for Reinforcement Learning.
ICML 2003: 162-169 |
4 | EE | Eyal Even-Dar,
Yishay Mansour:
Learning Rates for Q-learning.
Journal of Machine Learning Research 5: 1-25 (2003) |
2002 |
3 | EE | Eyal Even-Dar,
Shie Mannor,
Yishay Mansour:
PAC Bounds for Multi-armed Bandit and Markov Decision Processes.
COLT 2002: 255-270 |
2001 |
2 | EE | Eyal Even-Dar,
Yishay Mansour:
Learning Rates for Q-Learning.
COLT/EuroCOLT 2001: 589-604 |
1 | EE | Eyal Even-Dar,
Yishay Mansour:
Convergence of Optimistic and Incremental Q-Learning.
NIPS 2001: 1499-1506 |