NIPS Proceedingsβ

Nathan Srebro

11 Papers

  • Matrix reconstruction with the local max norm (2012)
  • Sparse Prediction with the $k$-Support Norm (2012)
  • Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm (2010)
  • Practical Large-Scale Optimization for Max-norm Regularization (2010)
  • Smoothness, Low Noise and Fast Rates (2010)
  • Tight Sample Complexity of Large-Margin Learning (2010)
  • Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data (2009)
  • Fast Rates for Regularized Objectives (2008)
  • Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices (2004)
  • Maximum-Margin Matrix Factorization (2004)
  • Linear Dependent Dimensionality Reduction (2003)