Discriminative approaches based on generative embeddings involve two key components: a generative model used to define the embedding; a discriminative learning ...

Feb 4, 2013 · We illustrate the performance of combining different generative embeddings with the IT kernels on different medical applications: colon cancer ...

This work has shown that a type of hybrid discriminative/generative approach has been recently shown to outperform classifiers obtained directly from the ...

Classical approaches to learn classifiers for structured objects (e.g., images, sequences) use generative models in a standard Bayesian framework.

We investigate the use of a recent family of non-extensive information theoretic kernels on the top of different generative embeddings.

On the Combination of Information-Theoretic Kernels with Generative Embeddings · In Similarity-Based Pattern Analysis and Recognition, Pelillo M. (ed.), pp. 67- ...

Using a generative embedding involves two steps: (i) defining and learning the generative model used to build the embedding; (ii) discriminatively learning a ( ...

Bibliographic details on On the Combination of Information-Theoretic Kernels with Generative Embeddings.

Using a generative embedding involves two steps: (i) defining and learning the generative model and using it to build the embedding; (ii) discriminatively ...

... Combining information theoretic kernels with generative embeddings for classification}, year={2013}, month={January}, volume={101}, number={1}, pages ...