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Axiomatic Properties of Negative Matrix Factorisation for Joint Sampling and Classification
Axiomatic Properties of Negative Matrix Factorisation for Joint Sampling and Classification – Neural inference in computer vision is a natural and successful method of modeling visual visual patterns. In this paper, we propose a supervised and semi-supervised framework to learn a representation of visual patterns from a set of visual patterns. Our proposed framework is […]