Robert M. Nishikawa

Statistical Learning Theory · 2002–2005

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Robert M. Nishikawa trusts overall

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

  1. C. Burges
  2. Yuhai Wu
  3. Christopher K. I. Williams
  4. David Ruppert
  5. Yoav Freund
  6. Issam El-Naqa
  7. Donald F. Specht
  8. George Eastman House

Who trusts Robert M. Nishikawa overall

  1. I. E. El Naqa
  2. Shijun Wang

Papers from Robert M. Nishikawa's perspective

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

  1. Statistical Learning Theory
  2. Advances in kernel methods: support vector learning
  3. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
  4. A Tutorial on Support Vector Machines for Pattern Recognition
  5. A decision-theoretic generalization of on-line learning and an application to boosting
  6. Neural Networks: A Comprehensive Foundation
  7. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  8. Sparse Bayesian Learning and the Relevan e Ve tor Ma hine
  9. Pattern Recognition and Neural Networks
  10. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS

Their papers