Searching for authors named "Shie Mannor" – sorted by Relevance.
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Reinforcement Learning for Average Reward Zero-Sum Games
- Reinforcement Learning for Average Reward Zero-Sum Games Shie Mannor Laboratory for Information
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Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
- , France Editor: Shie Mannor Abstract We study a variance reduction technique for Monte Carlo estimation
- Cited by 2 (0 self) – Add To MetaCart
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Adaptive timeout policies for fast finegrained power management
- Santa Clara, CA branislav.kveton@(email omitted); Shie Mannor Department of Electrical and Computer Engineering
- Cited by 1 (1 self) – Add To MetaCart
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On-line Learning with Imperfect Monitoring
- On-line Learning with Imperfect Monitoring Shie Mannor 1 and Nahum Shimkin 2 1 Laboratory
- Cited by 4 (1 self) – Add To MetaCart
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Weak Learners and Improved Rates of Convergence in Boosting
- Weak Learners and Improved Rates of Convergence in Boosting Shie Mannor and Ron Meir Department
- Cited by 4 (1 self) – Add To MetaCart
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Geometric Bounds for Generalization in Boosting
- Geometric Bounds for Generalization Boosting Shie Mannor and Department Electrical Engineering
- Cited by 1 (0 self) – Add To MetaCart
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Generalized Approachability Results for Stochastic Games with a Single Reachable State
- Generalized Approachability Results for Stochastic Games with a Single Reachable State Shie Mannor
- Cited by 3 (3 self) – Add To MetaCart
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The Steering Approach for Multi-Criteria Reinforcement Learning
- The Steering Approach for Multi-Criteria Reinforcement Learning Shie Mannor and Nahum Shimkin
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A Robust Geometric Approach to Multi-Criterion Reinforcement Learning
- A Robust Geometric Approach to Multi-Criterion Reinforcement Learning Shie Mannor shie
- Cited by 5 (1 self) – Add To MetaCart
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Adaptive Strategies and Regret Minimization in arbitrarily varying Markov Environments
- Adaptive Strategies and Regret Minimization in arbitrarily varying Markov Environments Shie Mannor
- Cited by 3 (0 self) – Add To MetaCart

