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All publications by Ron Meir
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A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
Yuval Harel, Ron Meir and Manfred Opper
Advances in Neural Information Processing Systems 28, 2015


Optimal Neural Codes for Control and Estimation
Alex K. Susemihl, Ron Meir and Manfred Opper
Advances in Neural Information Processing Systems 27, 2014


Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights
Daniel Soudry, Itay Hubara and Ron Meir
Advances in Neural Information Processing Systems 27, 2014


Analytical Results for the Error in Filtering of Gaussian Processes
Alex K. Susemihl, Ron Meir and Manfred Opper
Advances in Neural Information Processing Systems 24, 2011


Integrating Partial Model Knowledge in Model Free RL Algorithms
Aviv Tamar, Dotan D. Castro and Ron Meir
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
Dotan D. Castro, Dmitry Volkinshtein and Ron Meir
Advances in Neural Information Processing Systems 21, 2008


A neural network implementing optimal state estimation based on dynamic spike train decoding
Omer Bobrowski, Ron Meir, Shy Shoham and Yonina Eldar
Advances in Neural Information Processing Systems 20, 2007


Reinforcement learning with Gaussian processes
Yaakov Engel, Shie Mannor and Ron Meir
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound
Dori Peleg and Ron Meir
Advances in Neural Information Processing Systems 17, 2004


Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
Yaakov Engel, Shie Mannor and Ron Meir
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Error Bounds for Transductive Learning via Compression and Clustering
Philip Derbeko, Ran El-yaniv and Ron Meir
Advances in Neural Information Processing Systems 16, 2003


Generalization Error Bounds for Bayesian Mixture Algorithms
Ron Meir and Tong Zhang
Journal of Machine Learning Research, 2003


Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity
Shie Mannor, Ron Meir and Tong Zhang
Journal of Machine Learning Research, 2003


Data-Dependent Bounds for Bayesian Mixture Methods
Ron Meir and Tong Zhang
Advances in Neural Information Processing Systems 15, 2002