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arXiv · 1612.01397

Implicit Modeling -- A Generalization of Discriminative and Generative Approaches

Dmitrij Schlesinger·Carsten Rother
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Abstract

We propose a new modeling approach that is a generalization of generative and discriminative models. The core idea is to use an implicit parameterization of a joint probability distribution by specifying only the conditional distributions. The proposed scheme combines the advantages of both worlds -- it can use powerful complex discriminative models as its parts, having at the same time better generalization capabilities. We thoroughly evaluate the proposed method for a simple classification task with artificial data and illustrate its advantages for real-word scenarios on a semantic image segmentation problem.

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Dmitrij Schlesinger, Carsten Rother. 2016-12-05. Implicit Modeling -- A Generalization of Discriminative and Generative Approaches. https://arxiv.org/abs/1612.01397

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