Multiple Locally Linear Kernel Machines

2024/01/17 by David Picard, Picard, David
Computer Science · Engineering · #Face and Expression Recognition #Machine Learning and ELM #Sparse and Compressive Sensing Techniques

paper · pdf · doi:10.48550/arxiv.2401.09629

Abstract

In this paper we propose a new non-linear classifier based on a combination of locally linear classifiers. A well known optimization formulation is given as we cast the problem in a ℓ₁ Multiple Kernel Learning (MKL) problem using many locally linear kernels. Since the number of such kernels is huge, we provide a scalable generic MKL training algorithm handling streaming kernels. With respect to the inference time, the resulting classifier fits the gap between high accuracy but slow non-linear classifiers (such as classical MKL) and fast but low accuracy linear classifiers.

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