Linda Sellie

Statistical Learning Theory · 1992–2004

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 5 citations into it

Whom Linda Sellie trusts overall

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

1. David Haussler
2. Yoav Freund
3. Leslie G. Valiant
4. Robert E. Schapire
5. Michael Kearns
6. Anselm Blumer
7. Ming Li
8. Halbert White

Who trusts Linda Sellie overall

1. Vitaly Feldman
2. Adam Tauman Kalai
3. Daniel Alabi
4. Avrim Blum
5. Venkatesan Guruswami
6. Shai Shalev-Shwartz
7. Ilias Diakonikolas
8. Michael L. Littman
9. Philip M. Long
10. Stuart J. Russell

Papers from Linda Sellie's perspective

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

1. A theory of the learnable
2. Convergence of stochastic processes
3. On the learnability of Boolean formulae
4. ON CONVERGENCE OF STOCHASTIC PROCESSES
5. The Strength of Weak Learnability
6. Probability Inequalities for Sums of Bounded Random Variables
7. Learning in Artificial Neural Networks: A Statistical Perspective
8. Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications
9. Learning in the presence of malicious errors
10. Learning Disjunction of Conjunctions

Their papers

• Toward efficient agnostic learning (2004) — 452 citations
• Toward Efficient Agnostic Learning (1992)