Martin H. Anthony

Statistical Learning Theory · 1993–1999

A researcher in the Science corpus: 4 papers; trusts 4 researchers and is trusted by 150 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 8 citations into it

Whom Martin H. Anthony trusts overall

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

1. David Haussler
2. Vladimir Naumovich Vapnik
3. Leslie G. Valiant
4. Vladimir Naumovich Vapni

Who trusts Martin H. Anthony overall

1. Peter L. Bartlett
2. Andreas Maurer
3. Shahar Mendelson
4. Mark Bun
5. Steve Hanneke
6. Tong Zhang
7. Koby Crammer
8. Corinna Cortes
9. Maria-Florina Balcan
10. Sivan Sabato

Papers from Martin H. Anthony's perspective

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

1. A theory of the learnable
2. Convergence of stochastic processes
3. Quantifying Inductive Bias: AI Learning Algorithms and Valiant's Learning Framework
4. On the Density of Families of Sets
5. The Nature of Statistical Learning Theory
6. Minimum complexity density estimation
7. Learnability and the Vapnik-Chervonenkis dimension
8. Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm
9. Weak Convergence and Empirical Processes: With Applications to Statistics
10. A Result of Vapnik with Applications

Their papers

• Learning in Neural Networks: Theoretical Foundations (1999)
• Neural Network Learning: Theoretical Foundations (1999)
• Structural Risk Minimization Over Data-Dependent Hierarchies (1998)
• A Result of Vapnik with Applications (1993)