Marina Skurichina

Optimization & Training · 2002

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Marina Skurichina trusts overall

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

  1. Yoav Freund
  2. Thomas G. Dietterich
  3. Tin Kam Ho
  4. Robert E. Schapire
  5. Vladimir Naumovich Vapni
  6. Corinna Cortes
  7. Guozhong An
  8. Leo Breiman
  9. Vladimir Naumovich Vapnik
  10. Holger Schwenk

Who trusts Marina Skurichina overall

  1. Lior Rokach
  2. Anantha M. Prasad
  3. Thorsten Behrens
  4. Arnulf B. A. Graf
  5. Louis Iverson
  6. Olivier Bousquet
  7. A-Xing Zhu
  8. Abhijit Bendale
  9. Juliane Schäfer
  10. Andy Liaw

Papers from Marina Skurichina's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. The Nature of Statistical Learning Theory
  3. Gradient-based learning applied to document recognition
  4. A decision-theoretic generalization of on-line learning and an application to boosting
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Experiments with a New Boosting Algorithm
  8. Support-Vector Networks
  9. ImageNet: A large-scale hierarchical image database
  10. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization

Their papers