A. Gammerman

Artificial Intelligence · 1998–2005

A researcher in the Science corpus: 7 papers; trusts 5 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #3,786 of 35,345 by trust here, #9,870 by citations
• Scaling & Learning Theory — 8 citations into it
• Statistical Learning Theory — 6 citations into it; #245 of 1,038 by trust here, #314 by citations
• Control and Systems Engineering — 5 citations into it

Whom A. Gammerman trusts overall

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

1. Vladimir Naumovich Vapni
2. Yuhai Wu
3. Vladimir Naumovich Vapnik
4. Vladimir G Vovk
5. Craig John Saunders
6. Grace Wahba
7. Harris Drucker

Who trusts A. Gammerman overall

1. Vladimir G Vovk
2. Anastasios Nikolas Angelopoulos
3. Corinna Cortes
4. Yaniv Romano
5. Craig John Saunders
6. E.J. Candes
7. Stephen Bates
8. Johan A. K. Suykens
9. Mehryar Mohri
10. Nicolas Papernot

Papers from A. Gammerman's perspective

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

1. Statistical Learning Theory
2. Some results on Tchebycheffian spline functions
3. Spline Models for Observational Data
4. Learning by Transduction
5. Support Vector Regression Machines
6. Three approaches to the quantitative definition of information
7. Learning
8. Prediction, learning, and games
9. Introduction to algorithms
10. Testing Statistical Hypotheses

Their papers

• Algorithmic Learning in a Random World (2005) — 2,378 citations
• Inductive Confidence Machines for Regression (2002) — 690 citations
• On-line predictive linear regression (2005) — 108 citations
• Machine-Learning Applications of Algorithmic Randomness (1999)
• Transduction with Confidence and Credibility (1999)
• Learning by Transduction (1998)
• Ridge Regression Learning Algorithm in Dual Variables (1998)