R. Matousek

Computational Theory and Mathematics · 2022

A researcher in the Science corpus: 1 paper; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom R. Matousek trusts overall

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

  1. Donald R. Jones
  2. Eric R. Ziegel
  3. Joshua D. Knowles
  4. Vladimir Naumovich Vapni
  5. Hans-Martin Gutmann
  6. John R. Koza
  7. Jack P. C. Kleijnen
  8. G. De’ath
  9. Alexander I. J. Forrester
  10. James Kennedy

Papers from R. Matousek's perspective

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

  1. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
  2. The Elements of Statistical Learning
  3. A fast and elitist multiobjective genetic algorithm: NSGA-II
  4. The Nature of Statistical Learning Theory
  5. A Radial Basis Function Method for Global Optimization (Journal of Global Optimization)
  6. Greedy function approximation: A gradient boosting machine.
  7. ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems (IEEE Transactions on Evolutionary Computation)
  8. A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
  9. Efficient Global Optimization of Expensive Black-Box Functions
  10. The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations (SIAM Journal on Scientific Computing)

Their papers