1Learning Non-linear SVM in Input Space for Image Classification
Year: 2014
Type: article
Abstract: —The kernel trick enables learning of non-linear decision functions without having to explicitly map the original data to a high dimensional space. However, at test time, it requires evaluating the kernel with each one of the support vectors, which is time consuming. We propose a novel approach for learning non-linear support vector machine (SVM) corresponding to commonly used
Institutions: GREYC, Technicolor (France)
Language: English
Topic: Machine Learning and ELM
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2245625044