NDLI: Bayesian Ying-Yang system and theory as a unified statistical learning approach. IV. Further advances

Content Provider	IEEE Xplore Digital Library
Author	Lei Xu
Copyright Year	1998
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong (Lei Xu)
Abstract	A unified statistical learning approach called Bayesian Ying-Yang (BYY) system and theory has been developed by the present author in recent years. It functions as a general theory for supervised, unsupervised learning and semi-unsupervised extension for parameter learning, regularization, complexity selection, and architecture design. This paper reports several new advances: 1) the Ying dominated BYY learning are further discussed; 2) a general stochastic implementing procedure with detailed algorithms is proposed to overcome the difficulty encountered in the integral and summation operations such that the parameter learning and model selection become always implementable not only for the Yang dominated but also for the Ying dominated BYY learning; and 3) developments on BYY three-layer forward learning are provided, including new and simple criteria for the selection of the best hidden unit number and for the regularization of parameter learning.
Starting Page	1275
Ending Page	1280
File Size	698199
Page Count	6
File Format	PDF
ISBN	0780348591
ISSN	10987576
DOI	10.1109/IJCNN.1998.685958
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-05-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Statistical learning Unsupervised learning Principal component analysis Independent component analysis Supervised learning Machine learning Computer science Sampling methods Parametric statistics
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

Bayesian ying-yang system and theory as a unified statistical learning approach (i): for unsupervised and semi-unsupervised learning (1997).

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling (1997)

Bayesian Ying-Yang System and Theory as A Unified Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling (1997)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling (1997)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (I): for Unsupervised and Semi-Unsupervised Learning (0)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach: (III) Models and Algorithms for Dependence Reduction, Data Dimension Reduction, ICA and Supervised Learning (0)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach: (III) Models and Algorithms for Dependence Reduction, Data Dimension Reduction, ICA and Supervised Learning (0)

Bayesian Ying-Yang learning based ICA models

Bayesian Ying-Yang System and Theory as A Uni ed Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling ?

Bayesian Ying-Yang system and theory as a unified statistical learning approach. IV. Further advances

Similar Documents

Bayesian ying-yang system and theory as a unified statistical learning approach (i): for unsupervised and semi-unsupervised learning (1997).

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling (1997)

Bayesian Ying-Yang System and Theory as A Unified Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling (1997)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling (1997)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (I): for Unsupervised and Semi-Unsupervised Learning (0)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach: (III) Models and Algorithms for Dependence Reduction, Data Dimension Reduction, ICA and Supervised Learning (0)

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach: (III) Models and Algorithms for Dependence Reduction, Data Dimension Reduction, ICA and Supervised Learning (0)

Bayesian Ying-Yang learning based ICA models

Bayesian Ying-Yang System and Theory as A Uni ed Statistical Learning Approach (II): From Unsupervised Learning to Supervised Learning and Temporal Modeling ?

Bayesian Ying-Yang system and theory as a unified statistical learning approach. IV. Further advances