Nick Littlestone

Statistical Learning Theory · 1987–2003

A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 155 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 5 citations into it; #57 of 1,038 by trust here, #158 by citations

Whom Nick Littlestone trusts overall

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

1. Leslie G. Valiant
2. Temple F. Smith
3. Anselm Blumer
4. Vladimir Naumovich Vapnik
5. Michael Kearns
6. Andrzej Ehrenfeucht
7. David E. Rumelhart
8. David Haussler
9. Ming Li
10. Manfred K. Warmuth

Who trusts Nick Littlestone overall

1. Nicolò Cesa-Bianchi
2. Shai Shalev-Shwartz
3. Mario Marchand
4. Vitaly Feldman
5. Avrim Blum
6. Dan Roth
7. Ludmila I. Kuncheva
8. Charu C. Aggarwal
9. Elad Hazan
10. Yoav Freund

Papers from Nick Littlestone's perspective

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

1. A theory of the learnable
2. On the learnability of Boolean formulae
3. Pattern classification and scene analysis
4. Occam's Razor
5. A theory of the learnable
6. Parallel Distributed Processing: Explorations in the Microstructures of Cognition
7. Occam's razor
8. Learning Regular Sets from Queries and Counterexamples
9. Chervonenkis: On the uniform convergence of relative frequencies of events to their probabilities
10. Convergence of stochastic processes

Their papers

• Relating Data Compression and Learnability (2003) — 319 citations
• The weighted majority algorithm (1989)
• Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm (1987)