NIPS Proceedingsβ

Mario Marchand

10 Papers

  • Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks (2014)
  • From PAC-Bayes Bounds to KL Regularization (2009)
  • A PAC-Bayes Risk Bound for General Loss Functions (2006)
  • PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier (2006)
  • A PAC-Bayes approach to the Set Covering Machine (2005)
  • PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data (2004)
  • The Decision List Machine (2002)
  • Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks (1995)
  • Learning Stochastic Perceptrons Under k-Blocking Distributions (1994)
  • On Learning µ-Perceptron Networks with Binary Weights (1992)