D. Panchenko
Artificial Intelligence · 2002–2005
A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 87 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 13 citations into it; #2,034 of 35,345 by trust here, #5,533 by citations
- Statistics and Probability — 13 citations into it; #1,664 of 12,932 by trust here, #3,102 by citations
- Statistical Learning Theory — 8 citations into it; #167 of 1,038 by trust here, #229 by citations
Whom D. Panchenko trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Vladimir Koltchinskii
- Jerome H. Friedman
- Peter L. Bartlett
- Thomas Mikosch
- A. van der Vaart
- S. Jammalamadaka
- Andrew R. Barron
- Llew Mason
- Jon A. Wellner
- Yuhai Wu
Who trusts D. Panchenko overall
- Vladimir Koltchinskii
- Peter L. Bartlett
- Olivier Bousquet
- Corinna Cortes
- Stéphane Boucheron
- Yiming Ying
- Nati Srebro
- Gábor Lugosi
- Tengyuan Liang
- Yann LeCun
Papers from D. Panchenko's perspective
Ordered by how strongly the researchers D. Panchenko trusts endorse each paper. Same corpus, a different order for every researcher.
- Greedy function approximation: A gradient boosting machine.
- Special Invited Paper-Additive logistic regression: A statistical view of boosting
- A Probabilistic Theory of Pattern Recognition
- The Sample Complexity of Pattern Classification with Neural Networks: The Size of the Weights is More Important than the Size of the Network
- Functional Gradient Techniques for Combining Hypotheses
- Weak Convergence and Empirical Processes: With Applications to Statistics
- An Introduction to Probability Theory and Its Applications
- Rademacher penalties and structural risk minimization (IEEE Transactions on Information Theory)
- Uniform Central Limit Theorems: Contents
- Neural Network Learning: Theoretical Foundations
Their papers
- Empirical margin distributions and bounding the generalization error of combined classifiers (2002) — 596 citations
- Rademacher Processes and Bounding the Risk of Function Learning (2004) — 279 citations
- Risk bounds for mixture density estimation (2005) — 75 citations