2008 |
59 | | Branislav Kveton,
Jia Yuan Yu,
Georgios Theocharous,
Shie Mannor:
Online Learning with Expert Advice and Finite-Horizon Constraints.
AAAI 2008: 331-336 |
58 | EE | Constantine Caramanis,
Shie Mannor:
Learning in the Limit with Adversarial Disturbances.
COLT 2008: 467-478 |
57 | EE | Jia Yuan Yu,
Shie Mannor,
Nahum Shimkin:
Markov Decision Processes with Arbitrary Reward Processes.
EWRL 2008: 268-281 |
56 | EE | Kirill Dyagilev,
Shie Mannor,
Nahum Shimkin:
Efficient Reinforcement Learning in Parameterized Models: Discrete Parameter Case.
EWRL 2008: 41-54 |
55 | EE | Amir Massoud Farahmand,
Mohammad Ghavamzadeh,
Csaba Szepesvári,
Shie Mannor:
Regularized Fitted Q-Iteration: Application to Planning.
EWRL 2008: 55-68 |
54 | EE | Jordan Frank,
Shie Mannor,
Doina Precup:
Reinforcement learning in the presence of rare events.
ICML 2008: 336-343 |
53 | EE | Huan Xu,
Constantine Caramanis,
Shie Mannor:
Robust Regression and Lasso.
NIPS 2008: 1801-1808 |
52 | EE | Amir Massoud Farahmand,
Mohammad Ghavamzadeh,
Csaba Szepesvári,
Shie Mannor:
Regularized Policy Iteration.
NIPS 2008: 441-448 |
51 | EE | Esteban Arcaute,
Ramesh Johari,
Shie Mannor:
Local Two-Stage Myopic Dynamics for Network Formation Games.
WINE 2008: 263-277 |
50 | EE | Huan Xu,
Shie Mannor,
Constantine Caramanis:
Robustness, Risk, and Regularization in Support Vector Machines
CoRR abs/0803.3490: (2008) |
49 | EE | Huan Xu,
Constantine Caramanis,
Shie Mannor:
Robust Regression and Lasso
CoRR abs/0811.1790: (2008) |
2007 |
48 | | Branislav Kveton,
Prashant Gandhi,
Georgios Theocharous,
Shie Mannor,
Barbara Rosario,
Nilesh Shah:
Adaptive Timeout Policies for Fast Fine-Grained Power Management.
AAAI 2007: 1795-1800 |
47 | | Chih-Han Yu,
Shie Mannor,
Georgios Theocharous,
Avi Pfeffer:
User Model and Utility Based Power Management.
AAAI 2007: 1918-1919 |
46 | EE | Gábor Lugosi,
Shie Mannor,
Gilles Stoltz:
Strategies for Prediction Under Imperfect Monitoring.
COLT 2007: 248-262 |
45 | EE | Benoît Châtelain,
Shie Mannor,
François Gagnon,
David V. Plant:
Non-Cooperative Design of Translucent Networks.
GLOBECOM 2007: 2348-2352 |
44 | EE | Erick Delage,
Shie Mannor:
Percentile optimization in uncertain Markov decision processes with application to efficient exploration.
ICML 2007: 225-232 |
43 | EE | Saeed Sharifi Tehrani,
Shie Mannor,
Warren J. Gross:
Survey of Stochastic Computation on Factor Graphs.
ISMVL 2007: 54 |
42 | EE | Fariba Heidari,
Shie Mannor,
Lorne Mason:
Reinforcement Learning-Based Load Shared Sequential Routing.
Networking 2007: 832-843 |
41 | EE | Esteban Arcaute,
Ramesh Johari,
Shie Mannor:
Network Formation: Bilateral Contracting and Myopic Dynamics.
WINE 2007: 191-207 |
40 | EE | Shie Mannor,
Jeff S. Shamma:
Multi-agent learning for engineers.
Artif. Intell. 171(7): 417-422 (2007) |
39 | EE | Gábor Lugosi,
Shie Mannor,
Gilles Stoltz:
Strategies for prediction under imperfect monitoring
CoRR abs/math/0701419: (2007) |
38 | EE | Jia Yuan Yu,
Shie Mannor:
Efficiency of Market-Based Resource Allocation among Many Participants.
IEEE Journal on Selected Areas in Communications 25(6): 1244-1259 (2007) |
37 | EE | Constantine Caramanis,
Shie Mannor:
An Inequality for Nearly Log-Concave Distributions With Applications to Learning.
IEEE Transactions on Information Theory 53(3): 1043-1057 (2007) |
36 | EE | Shie Mannor,
Jeff S. Shamma,
Gürdal Arslan:
Online calibrated forecasts: Memory efficiency versus universality for learning in games.
Machine Learning 67(1-2): 77-115 (2007) |
2006 |
35 | EE | Shie Mannor,
Nahum Shimkin:
Online Learning with Variable Stage Duration.
COLT 2006: 408-422 |
34 | EE | Shie Mannor,
John N. Tsitsiklis:
Online Learning with Constraints.
COLT 2006: 529-543 |
33 | EE | Philipp W. Keller,
Shie Mannor,
Doina Precup:
Automatic basis function construction for approximate dynamic programming and reinforcement learning.
ICML 2006: 449-456 |
32 | EE | Jia Yuan Yu,
Shie Mannor:
Asymptotics of Efficiency Loss in Competitive Market Mechanisms.
INFOCOM 2006 |
31 | EE | Huan Xu,
Shie Mannor:
The Robustness-Performance Tradeoff in Markov Decision Processes.
NIPS 2006: 1537-1544 |
30 | 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 |
29 | EE | Yaakov Engel,
Shie Mannor,
Ron Meir:
Reinforcement learning with Gaussian processes.
ICML 2005: 201-208 |
28 | EE | Shie Mannor,
Dori Peleg,
Reuven Y. Rubinstein:
The cross entropy method for classification.
ICML 2005: 561-568 |
27 | | Ion Muslea,
Virginia Dignum,
Daniel D. Corkill,
Catholijn M. Jonker,
Frank Dignum,
Silvia Coradeschi,
Alessandro Saffiotti,
Dan Fu,
Jeff Orkin,
William Cheetham,
Kai Goebel,
Piero P. Bonissone,
Leen-Kiat Soh,
Randolph M. Jones,
Robert E. Wray III,
Matthias Scheutz,
Daniela Pucci de Farias,
Shie Mannor,
Georgios Theocharous,
Doina Precup,
Bamshad Mobasher,
Sarabjot S. Anand,
Bettina Berendt,
Andreas Hotho,
Hans W. Guesgen,
Michael T. Rosenstein,
Mohammad Ghavamzadeh:
The Workshop Program at the Nineteenth National Conference on Artificial Intelligence.
AI Magazine 26(1): 103-108 (2005) |
26 | EE | Pieter-Tjerk de Boer,
Dirk P. Kroese,
Shie Mannor,
Reuven Y. Rubinstein:
A Tutorial on the Cross-Entropy Method.
Annals OR 134(1): 19-67 (2005) |
25 | EE | Ishai Menache,
Shie Mannor,
Nahum Shimkin:
Basis Function Adaptation in Temporal Difference Reinforcement Learning.
Annals OR 134(1): 215-238 (2005) |
24 | EE | Ramesh Johari,
Shie Mannor,
John N. Tsitsiklis:
Efficiency Loss in a Network Resource Allocation Game: The Case of Elastic Supply
CoRR abs/cs/0506054: (2005) |
2004 |
23 | EE | Shie Mannor:
Reinforcement Learning for Average Reward Zero-Sum Games.
COLT 2004: 49-63 |
22 | EE | Constantine Caramanis,
Shie Mannor:
An Inequality for Nearly Log-Concave Distributions with Applications to Learning.
COLT 2004: 534-548 |
21 | EE | Shie Mannor,
Duncan Simester,
Peng Sun,
John N. Tsitsiklis:
Bias and variance in value function estimation.
ICML 2004 |
20 | EE | Shie Mannor,
Ishai Menache,
Amit Hoze,
Uri Klein:
Dynamic abstraction in reinforcement learning via clustering.
ICML 2004 |
19 | EE | Shie Mannor,
Nahum Shimkin:
A Geometric Approach to Multi-Criterion Reinforcement Learning.
Journal of Machine Learning Research 5: 325-360 (2004) |
18 | EE | Shie Mannor,
John N. Tsitsiklis:
The Sample Complexity of Exploration in the Multi-Armed Bandit Problem.
Journal of Machine Learning Research 5: 623-648 (2004) |
2003 |
17 | EE | Shie Mannor,
John N. Tsitsiklis:
Lower Bounds on the Sample Complexity of Exploration in the Multi-armed Bandit Problem.
COLT 2003: 418-432 |
16 | EE | Shie Mannor,
Nahum Shimkin:
On-Line Learning with Imperfect Monitoring.
COLT 2003: 552-566 |
15 | | Yaakov Engel,
Shie Mannor,
Ron Meir:
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning.
ICML 2003: 154-161 |
14 | | Eyal Even-Dar,
Shie Mannor,
Yishay Mansour:
Action Elimination and Stopping Conditions for Reinforcement Learning.
ICML 2003: 162-169 |
13 | | Shie Mannor,
Reuven Y. Rubinstein,
Yohai Gat:
The Cross Entropy Method for Fast Policy Search.
ICML 2003: 512-519 |
12 | EE | Shie Mannor,
Ron Meir,
Tong Zhang:
Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity.
Journal of Machine Learning Research 4: 713-741 (2003) |
11 | EE | Shie Mannor,
Nahum Shimkin:
The Empirical Bayes Envelope and Regret Minimization in Competitive Markov Decision Processes.
Math. Oper. Res. 28(2): 327-345 (2003) |
2002 |
10 | EE | Eyal Even-Dar,
Shie Mannor,
Yishay Mansour:
PAC Bounds for Multi-armed Bandit and Markov Decision Processes.
COLT 2002: 255-270 |
9 | EE | Shie Mannor,
Ron Meir,
Tong Zhang:
The Consistency of Greedy Algorithms for Classification.
COLT 2002: 319-333 |
8 | EE | Ishai Menache,
Shie Mannor,
Nahum Shimkin:
Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning.
ECML 2002: 295-306 |
7 | EE | Yaakov Engel,
Shie Mannor,
Ron Meir:
Sparse Online Greedy Support Vector Regression.
ECML 2002: 84-96 |
6 | | Shie Mannor,
Ron Meir:
On the Existence of Linear Weak Learners and Applications to Boosting.
Machine Learning 48(1-3): 219-251 (2002) |
2001 |
5 | EE | Shie Mannor,
Nahum Shimkin:
Adaptive Strategies and Regret Minimization in Arbitrarily Varying Markov Environments.
COLT/EuroCOLT 2001: 128-142 |
4 | EE | Shie Mannor,
Ron Meir:
Geometric Bounds for Generalization in Boosting.
COLT/EuroCOLT 2001: 461-472 |
3 | | Yaakov Engel,
Shie Mannor:
Learning Embedded Maps of Markov Processes.
ICML 2001: 138-145 |
2 | EE | Shie Mannor,
Nahum Shimkin:
The Steering Approach for Multi-Criteria Reinforcement Learning.
NIPS 2001: 1563-1570 |
2000 |
1 | | Shie Mannor,
Ron Meir:
Weak Learners and Improved Rates of Convergence in Boosting.
NIPS 2000: 280-286 |