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- 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)

- 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)

- 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)

- Yaakov Engel, Shie Mannor, Ron Meir
- ICML
- 2005

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)

- 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)

- 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)

- 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)

- 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)

- 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)

- Yaakov Engel, Shie Mannor, Ron Meir
- ICML
- 2003

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)