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» Evolving kernels for support vector machine classification
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IJCNN
2007
IEEE
15 years 10 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
DAGM
2010
Springer
15 years 5 months ago
Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma
Abstract. We consider an automated processing pipeline for tissue micro array analysis (TMA) of renal cell carcinoma. It consists of several consecutive tasks, which can be mapped ...
Peter J. Schüffler, Thomas J. Fuchs, Cheng So...
ECAI
2006
Springer
15 years 8 months ago
Semantic Tree Kernels to Classify Predicate Argument Structures
Recent work on Semantic Role Labeling (SRL) has shown that syntactic information is critical to detect and extract predicate argument structures. As syntax is expressed by means of...
Alessandro Moschitti, Bonaventura Coppola, Daniele...
ICRA
2006
IEEE
99views Robotics» more  ICRA 2006»
15 years 10 months ago
Human Motion Recognition with a Convolution Kernel
Abstract— We address the problem of human motion recognition in this paper. The goal of human motion recognition is to recognize the type of motion recorded in a video clip, whic...
Dongwei Cao, Osama Masoud, Daniel Boley
ICML
2008
IEEE
16 years 5 months ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...