NIPS Proceedingsβ

Olivier Chapelle

18 Papers

  • An Empirical Evaluation of Thompson Sampling (2011)
  • Large Margin Taxonomy Embedding for Document Categorization (2008)
  • Tighter Bounds for Structured Estimation (2008)
  • A General Boosting Method and its Application to Learning Ranking Functions for Web Search (2007)
  • An Analysis of Inference with the Universum (2007)
  • Learning with Transformation Invariant Kernels (2007)
  • An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models (2006)
  • Branch and Bound for Semi-Supervised Support Vector Machines (2006)
  • Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions (2006)
  • A Machine Learning Approach to Conjoint Analysis (2004)
  • Measure Based Regularization (2003)
  • Cluster Kernels for Semi-Supervised Learning (2002)
  • Kernel Dependency Estimation (2002)
  • Incorporating Invariances in Non-Linear Support Vector Machines (2001)
  • Feature Selection for SVMs (2000)
  • Vicinal Risk Minimization (2000)
  • Model Selection for Support Vector Machines (1999)
  • Transductive Inference for Estimating Values of Functions (1999)