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)

iWML_2016_paper_25.pdf - Accepted Version

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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 CreatorsORCiD
Balasubramanian, Vineeth NUNSPECIFIED
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://raiith.iith.ac.in/id/eprint/2551
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