Isabelle M. Pelaschier

Artificial Intelligence · 2014

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Isabelle M. Pelaschier trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Bernhard Schölkopf
  2. Vladimir Naumovich Vapni
  3. K. Müller
  4. James Franklin
  5. Fabrizio Sebastiani

Papers from Isabelle M. Pelaschier's perspective

Ordered by how strongly the researchers Isabelle M. Pelaschier trusts endorse each paper. Same corpus, a different order for every researcher.

  1. The Nature of Statistical Learning Theory
  2. Learning with Kernels: support vector machines, regularization, optimization, and beyond
  3. Theory of Reproducing Kernels.
  4. Nonlinear Component Analysis as a Kernel Eigenvalue Problem
  5. Machine learning for medical diagnosis: history, state of the art and perspective
  6. The connection between regularization operators and support vector kernels
  7. Machine learning in automated text categorization
  8. An introduction to kernel-based learning algorithms
  9. Asymptotic statistical theory of overtraining and cross-validation
  10. Functions of Positive and Negative Type, and their Connection with the Theory of Integral Equations

Their papers