Manifold-Based Inference for a Supervised Gaussian Process Classifier

Anis Fradi; Chafik Samir; Anne-Françoise Yao

ICASSP 2018accepted0 citations

Manifold-Based Inference for a Supervised Gaussian Process Classifier

Anis Fradi, Chafik Samir, Anne-Françoise Yao

Abstract

One of the challenging classification problems consists of learning relevant and meaningful relationships between high dimensional representations across a relatively few observed individuals. Since this problem could have drastic effects on the classification performance, we propose a Bayesian alternative in the case of logistic regression. The proposed method has the additional benefit to learn both the adaptive embedding, as a Gaussian process, and the dimensionality reduction, jointly within the same Bayesian framework. We illustrate the efficiency and the accuracy of our framework for classifying images of manufacturing defects.

BibTeX

@inproceedings{icassp2018_manifoldbasedinf,
  title = {Manifold-Based Inference for a Supervised Gaussian Process Classifier},
  author = {Anis Fradi and Chafik Samir and Anne-Françoise Yao},
  booktitle = {ICASSP 2018},
  year = {2018}
}