NIPS Proceedingsβ

Ron Meir

14 Papers

  • A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding (2015)
  • Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights (2014)
  • Optimal Neural Codes for Control and Estimation (2014)
  • Analytical Results for the Error in Filtering of Gaussian Processes (2011)
  • Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation (2008)
  • A neural network implementing optimal state estimation based on dynamic spike train decoding (2007)
  • A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound (2004)
  • Error Bounds for Transductive Learning via Compression and Clustering (2003)
  • Data-Dependent Bounds for Bayesian Mixture Methods (2002)
  • Weak Learners and Improved Rates of Convergence in Boosting (2000)
  • Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks (1998)
  • On the Optimality of Incremental Neural Network Algorithms (1998)
  • Structural Risk Minimization for Nonparametric Time Series Prediction (1997)
  • Time Series Prediction using Mixtures of Experts (1996)