NIPS Proceedingsβ

Peter Sollich

14 Papers

  • Learning curves for multi-task Gaussian process regression (2012)
  • Exact learning curves for Gaussian process regression on large random graphs (2010)
  • Kernels and learning curves for Gaussian process regression on random graphs (2009)
  • Using the Equivalent Kernel to Understand Gaussian Process Regression (2004)
  • Gaussian Process Regression with Mismatched Models (2001)
  • Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks (1999)
  • Probabilistic Methods for Support Vector Machines (1999)
  • Learning Curves for Gaussian Processes (1998)
  • On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories (1998)
  • On-line Learning from Finite Training Sets in Nonlinear Networks (1997)
  • Online Learning from Finite Training Sets: An Analytical Case Study (1996)
  • Learning with ensembles: How overfitting can be useful (1995)
  • Learning from queries for maximum information gain in imperfectly learnable problems (1994)
  • Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world (1994)