Convex support and Relevance Vector Machines for selective multimodal pattern recognition

We address the problem of featureless pattern recognition under the assumption that pair-wise comparison of objects is arbitrarily scored by real numbers. Such a linear embedding is much more general than the traditional kernel-based approach, which demands positive semi-definiteness of the matrix o...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Seredin, O., Mottl, V., Tatarchuk, A., Razin, N., Windridge, D.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Hilbert space Kernel Pattern recognition Support vector machines Training Vectors
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