NDLI: Auto-Tuning Kernel Mean Matching

Content Provider	IEEE Xplore Digital Library
Author	Yun-Qian Miao Farahat, A.K. Kamel, M.S.
Copyright Year	2013
Description	Author affiliation: Univ. of Waterloo, Waterloo, ON, Canada (Yun-Qian Miao; Farahat, A.K.; Kamel, M.S.)
Abstract	The Kernel Mean Matching (KMM) algorithm is a mathematically rigorous method that directly weights the training samples such that the mean discrepancy in a kernel space is minimized. However, the applicability of KMM is still limited, due to the existence of many parameters that are difficult to adjust. This paper presents a novel method that automatically tunes the KMM parameters by assessing the quality of distribution matching from a new perspective. While the KMM itself minimizes the mean discrepancy in a reproducing kernel Hilbert space, the tuning of KMM is achieved by adopting a different quality measure which reflects the Normalized Mean Squared Error (NMSE) between the estimated importance weights and the ratio of the estimated test and training densities. This method enables the applicability of KMM to real domains and leads to a generalized routine for the KMM to incorporate different types of kernels. The effectiveness of the proposed method is demonstrated by experiments on both synthetic and benchmark datasets.
Sponsorship	Toshiba
Starting Page	560
Ending Page	567
File Size	350680
Page Count	8
File Format	PDF
e-ISBN	9781479931422
DOI	10.1109/ICDMW.2013.117
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Adaptation models Measurement uncertainty Estimation Covariate Shift Adaptation Benchmark testing Kernel Mean Matching Density-ratio Estimation Kernel Tuning
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

Intrusion detection under covariate shift using modified support vector machine and modified backpropagation

Direct importance estimation for covariate shift adaptation

Large-scale covariate shift adaptation (2007).

Direct density ratio estimation for large-scale covariate shift adaptation (2008)

Direct density ratio estimation for large-scale covariate shift adaptation (2009)

Ensemble Kernel Mean Matching

Covariate Shift by Kernel Mean Matching

Covariate shift by kernel mean matching.

1 direct density ratio estimation for large-scale covariate shift adaptation.

Auto-Tuning Kernel Mean Matching

Similar Documents

Intrusion detection under covariate shift using modified support vector machine and modified backpropagation

Direct importance estimation for covariate shift adaptation

Large-scale covariate shift adaptation (2007).

Direct density ratio estimation for large-scale covariate shift adaptation (2008)

Direct density ratio estimation for large-scale covariate shift adaptation (2009)

Ensemble Kernel Mean Matching

Covariate Shift by Kernel Mean Matching

Covariate shift by kernel mean matching.

1 direct density ratio estimation for large-scale covariate shift adaptation.

Auto-Tuning Kernel Mean Matching