T
Thomas Gärtner
Researcher at University of Nottingham
Publications - 66
Citations - 4024
Thomas Gärtner is an academic researcher from University of Nottingham. The author has contributed to research in topics: Kernel method & Support vector machine. The author has an hindex of 20, co-authored 66 publications receiving 3729 citations. Previous affiliations of Thomas Gärtner include University of Bristol & Fraunhofer Society.
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Book ChapterDOI
On Graph Kernels: Hardness Results and Efficient Alternatives
TL;DR: As most ‘real-world’ data is structured, research in kernel methods has begun investigating kernels for various kinds of structured data, but only very specific graphs such as trees and strings have been considered.
Proceedings Article
Multi-Instance Kernels
TL;DR: A kernel on multi-instance data that can be shown to separate positive and negative sets under natural assumptions is shown and compares favorably with state of the art multi- instance learning algorithms in an empirical study.
Journal ArticleDOI
A survey of kernels for structured data
TL;DR: This survey describes several approaches of defining positive definite kernels on structured instances directly on the basis of areal vector space and thus in a single table.
Proceedings ArticleDOI
Cyclic pattern kernels for predictive graph mining
TL;DR: The experimental results show that cyclic pattern kernels can be computed quickly and offer predictive performance superior to recent graph kernels based on frequent patterns.
Journal ArticleDOI
Kernels and Distances for Structured Data
TL;DR: A general method for constructing a kernel following the syntactic structure of the data, as defined by its type signature in a higher-order logic, and the main theoretical result is the positive definiteness of any kernel thus defined.