Kevin Ying

Molecular Biology · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kevin Ying trusts

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

  1. Gordon K. Smyth (in Molecular Biology)
  2. Teuvo Kohonen (in Representation & Self-Supervised Learning)
  3. Peter J. Rousseeuw (in Evaluation & Benchmarks)
  4. Andrew P. Bradley (in Evaluation & Benchmarks)

Papers from Kevin Ying's perspective

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

  1. Gradient-based learning applied to document recognition
  2. Regression Shrinkage and Selection via the Lasso
  3. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  4. Controlling the false discovery rate: a practical and powerful approach to multiple testing
  5. Learning representations by back-propagating errors
  6. Visualizing Data using t-SNE
  7. Estimating the Dimension of a Model
  8. A training algorithm for optimal margin classifiers
  9. Ridge Regression: Biased Estimation for Nonorthogonal Problems
  10. From the Cover: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Their papers