NDLI: Ensemble Kernel Mean Matching

Content Provider	IEEE Xplore Digital Library
Author	Yun-Qian Miao Farahat, A.K. Kamel, M.S.
Copyright Year	2015
Description	Author affiliation: Univ. of Waterloo Waterloo, Waterloo, ON, Canada (Yun-Qian Miao; Farahat, A.K.; Kamel, M.S.)
Abstract	The Kernel Mean Matching (KMM) is an elegant algorithm that produces density ratios between training and test data by minimizing their maximum mean discrepancy in a kernel space. The applicability of KMM to large-scale problems is however hindered by the quadratic complexity of calculating and storing the kernel matrices over training and test data. To address this problem, this paper proposes a novel ensemble algorithm for KMM, which divides test samples into smaller partitions, estimates a density ratio for each partition and then fuses these local estimates with a weighted sum. Our theoretical analysis shows that the ensemble KMM has a lower error bound than the centralized KMM, which uses all the test data at once to estimate the density ratio. Considering its suitability for distributed implementation, the proposed algorithm is also favorable in terms of time and space complexities. Experiments on benchmark datasets confirm the superiority of the proposed algorithm in terms of estimation accuracy and running time.
Starting Page	330
Ending Page	338
File Size	1792169
Page Count	9
File Format	PDF
ISSN	15504786
e-ISBN	9781467395045
DOI	10.1109/ICDM.2015.127
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Training Partitioning algorithms Estimation Complexity theory Density functional theory Algorithm design and analysis Distributed algorithm Density ratio estimation Kernel mean matching Ensemble method
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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