Shie Mannor

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The kernel recursive least-squares algorithm

Yaakov Engel, Shie Mannor, Ron Meir
IEEE Transactions on Signal Processing
2004

We present a nonlinear version of the recursive least squares (RLS) algorithm. Our algorithm performs linear regression in a high-dimensional feature space induced by a Mercer kernel and can… (More)

A Tutorial on the Cross-Entropy Method

Pieter-Tjerk de Boer, Dirk P. Kroese, Shie Mannor, Reuven Y. Rubinstein
Annals OR
2005

The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tutorial is to give a gentle introduction to… (More)

Efficiency loss in a network resource allocation game: the case of elastic supply

Ramesh Johari, Shie Mannor, John N. Tsitsiklis
IEEE Transactions on Automatic Control
2004

We consider a resource allocation problem where individual users wish to send data across a network to maximize their utility, and a cost is incurred at each link that depends on the total rate sent… (More)

Reinforcement learning with Gaussian processes

Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framework by addressing… (More)

PAC Bounds for Multi-armed Bandit and Markov Decision Processes

Eyal Even-Dar, Shie Mannor, Yishay Mansour
COLT
2002

The bandit problem is revisited and considered under the PAC model. Our main contribution in this part is to show that given n arms, it suffices to pull the arms O( n 2 log 1 δ ) times to find an… (More)

The Sample Complexity of Exploration in the Multi-Armed Bandit Problem

Shie Mannor, John N. Tsitsiklis
Journal of Machine Learning Research
2003

We consider the multi-armed bandit problem under the PAC (“probably approximately correct”) model. It was shown by Even-Dar et al. (2002) that given n arms, a total of O ( (n/ε2) log(1/δ) ) trials… (More)

Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems

Eyal Even-Dar, Shie Mannor, Yishay Mansour
Journal of Machine Learning Research
2006

We incorporate statistical confidence intervals in both the multi-armed bandit and the reinforcement learning problems. In the bandit problem we show that given n arms, it suffices to pull the arms a… (More)

Robustness and Regularization of Support Vector Machines

Huan Xu, Constantine Caramanis, Shie Mannor
Journal of Machine Learning Research
2009

We consider regularized support vector machines (SVMs) and show that they are precisely equivalent to a new robust optimization formulation. We show that t is equivalence of robust optimization and… (More)

Robustness and generalization

Huan Xu, Shie Mannor
Machine Learning
2011

We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is “similar” to a training sample, then the testing error is close to the… (More)

Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning

We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by imposing a Gaussian… (More)

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