Dissimilarity Based Contrastive Divergence for Anomaly Detection

Manocha, S and Adepu, R S and Balasubramanian, Vineeth N (2016) Dissimilarity Based Contrastive Divergence for Anomaly Detection. In: 2nd Indian Workshop on Machine Learning, IIT Kanpur. (Submitted)

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Abstract

This paper describes training of a Re- stricted Boltzmann Machine(RBM) using dissimilarity-based contrastive divergence to obtain an anomaly detector. We go over the merits of the method over other approaches and describe the method's usefulness to ob- tain a generative model.

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IITH Creators:	IITH Creators ORCiD Balasubramanian, Vineeth N UNSPECIFIED
Item Type:	Conference or Workshop Item (Paper)
Subjects:	Computer science > Big Data Analytics
Divisions:	Department of Computer Science & Engineering
Depositing User:	Team Library
Date Deposited:	20 Jul 2016 07:26
Last Modified:	25 Apr 2018 05:41
URI:	http://raiithold.iith.ac.in/id/eprint/2551
Publisher URL:
Related URLs:	Google Scholar

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