Paul Duncan
Artificial Intelligence · 2014
A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 11 citations into it
- Statistical Learning Theory — 9 citations into it
Whom Paul Duncan trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Vladimir Naumovich Vapni (in Artificial Intelligence)
- Fabrizio Sebastiani (in Artificial Intelligence)
- James Franklin (in Statistical Learning Theory)
Papers from Paul Duncan's perspective
Ordered by how strongly the researchers Paul Duncan trusts endorse each paper. Same corpus, a different order for every researcher.
- The Nature of Statistical Learning Theory
- Learning with Kernels: support vector machines, regularization, optimization, and beyond
- Theory of Reproducing Kernels.
- Machine learning for medical diagnosis: history, state of the art and perspective
- Nonlinear Component Analysis as a Kernel Eigenvalue Problem
- The connection between regularization operators and support vector kernels
- Machine learning in automated text categorization
- An introduction to kernel-based learning algorithms
- Asymptotic statistical theory of overtraining and cross-validation
- Functions of Positive and Negative Type, and their Connection with the Theory of Integral Equations
Their papers
- Understanding Machine-learned Density Functionals (2014) — 164 citations