NDLI: Divide and Conquer Strategies for MLP Training

Content Provider	IEEE Xplore Digital Library
Author	Bhagat, S. Deodhare, D.
Copyright Year	2006
Description	Author affiliation: Rutgers Univ., New Brunswick (Bhagat, S.)
Abstract	Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in the data sets. However, the sheer volume of available data and its dimensionality makes data exploration a challenge. Employing neural network training paradigms in such domains can prove to be prohibitively expensive. An algorithm, originally proposed for supervised on-line learning, has been improvised upon to make it suitable for deployment in large volume, high-dimensional domains. The basic strategy is to divide the data into manageable subsets or blocks and maintain multiple copies of a neural network with each copy training on a different block. A method to combine the results has been defined in such a way that convergence towards stationary points of the global error function can be guaranteed. A parallel algorithm has been implemented on a Linux-based cluster. Experimental results on popular benchmarks have been included to endorse the efficacy of our implementation.
Starting Page	3415
Ending Page	3420
File Size	144473
Page Count	6
File Format	PDF
ISBN	0780394909
DOI	10.1109/IJCNN.2006.247344
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-16
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Management training Convergence Space technology Lagrangian functions Parallel algorithms Explosives Computer networks Gradient methods Computer science
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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