Lawrence Kai Shih

International Conference on Machine Learning · 2003

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

Whom Lawrence Kai Shih trusts overall

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

  1. David E. Heckerman
  2. Yiming Yang

Who trusts Lawrence Kai Shih overall

  1. John Anvik
  2. Burr Settles
  3. Tomas Pranckevičius
  4. Nicholas Lourie
  5. Ping Li
  6. Ignazio Pillai
  7. Rion Snow
  8. Pietro Panzarasa
  9. Rasmus Elsborg Madsen
  10. Liangxiao Jiang

Papers from Lawrence Kai Shih's perspective

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

  1. Text Categorization with Support Vector Machines: Learning with Many Relevant Features
  2. Term-Weighting Approaches in Automatic Text Retrieval
  3. A comparison of event models for naive bayes text classification
  4. A re-examination of text categorization methods
  5. Text Categorization Based on Regularized Linear Classification Methods (Information retrieval (Boston))
  6. Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
  7. Pattern classification and scene analysis
  8. A Tutorial on Learning with Bayesian Networks
  9. A statistical interpretation of term specificity and its application in retrieval
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers