Cheol-Koo Lee

Artificial Intelligence · 2000–2004

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it; #33,779 of 35,345 by trust here, #24,417 by citations
• Statistics and Probability — 7 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Cheol-Koo Lee trusts overall

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

1. Grace Wahba
2. Dustin Boswell
3. Koby Crammer
4. Yuh-Jye Lee
5. Yoram Singer
6. Olvi L. Mangasarian

Who trusts Cheol-Koo Lee overall

1. Sara N. Burke
2. Matthias W. Seeger
3. Ambuj Tewari
4. Javier M. Moguerza
5. Lifeng Wang
6. David B. Allison
7. Ü. Dogan
8. B. '. Pires
9. Toren Finkel
10. C. A. Barnes

Papers from Cheol-Koo Lee's perspective

Ordered by how strongly the researchers Cheol-Koo Lee trusts endorse each paper. Same corpus, a different order for every researcher.

1. Introduction to Support Vector Machines
2. Spline Models for Observational Data
3. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
4. On the Influence of the Kernel on the Consistency of Support Vector Machines
5. On the Learnability and Design of Output Codes for Multiclass Problems
6. SSVM: A Smooth Support Vector Machine for Classification (Computational optimization and applications)
7. Theory of point estimation
8. The jackknife, the bootstrap, and other resampling plans
9. Gene-expression profile of the ageing brain in mice (Nature Genetics)
10. The Nature of Statistical Learning Theory

Their papers

• Multicategory Support Vector Machines , Theory , and Application to the Classification of Microarray Data and Satellite Radiance Data (2004)
• A mixture model approach for the analysis of microarray gene expression data (2002) — 390 citations
• Gene-expression profile of the ageing brain in mice (2000) — 1,085 citations