Dae-Won Kim

Artificial Intelligence · 2013

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

Subfields

Whom Dae-Won Kim trusts overall

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

  1. Yiming Yang

Papers from Dae-Won Kim's perspective

Ordered by how strongly the researchers Dae-Won Kim trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Machine learning in automated text categorization
  2. BoosTexter: A Boosting-based System for Text Categorization (Machine-mediated learning)
  3. A Comparative Study on Feature Selection in Text Categorization
  4. RCV1: A New Benchmark Collection for Text Categorization Research
  5. Learning multi-label scene classification (Pattern Recognition)
  6. An Introduction to Variable and Feature Selection
  7. A review of feature selection techniques in bioinformatics
  8. Gradient-based learning applied to document recognition
  9. ImageNet classification with deep convolutional neural networks
  10. Text Categorization with Support Vector Machines: Learning with Many Relevant Features

Their papers