Online Manifold Regularization by Dual Ascending Procedure

We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dua...

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Main Authors: Boliang Sun, Guohui Li, Li Jia, Hui Zhang
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/838439
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spelling doaj-df2cfb1c64544ada863d6e999a83100f2020-11-25T01:02:53ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/838439838439Online Manifold Regularization by Dual Ascending ProcedureBoliang Sun0Guohui Li1Li Jia2Hui Zhang3Department of Information System and Management, National University of Defense Technology, Hunan, Changsha 410073, ChinaDepartment of Information System and Management, National University of Defense Technology, Hunan, Changsha 410073, ChinaDepartment of Information System and Management, National University of Defense Technology, Hunan, Changsha 410073, ChinaDepartment of Information System and Management, National University of Defense Technology, Hunan, Changsha 410073, ChinaWe propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approaches. An important conclusion is that our online MR algorithms can handle the settings where the target hypothesis is not fixed but drifts with the sequence of examples. We also recap and draw connections to earlier works. This paper paves a way to the design and analysis of online manifold regularization algorithms.http://dx.doi.org/10.1155/2013/838439
collection DOAJ
language English
format Article
sources DOAJ
author Boliang Sun
Guohui Li
Li Jia
Hui Zhang
spellingShingle Boliang Sun
Guohui Li
Li Jia
Hui Zhang
Online Manifold Regularization by Dual Ascending Procedure
Mathematical Problems in Engineering
author_facet Boliang Sun
Guohui Li
Li Jia
Hui Zhang
author_sort Boliang Sun
title Online Manifold Regularization by Dual Ascending Procedure
title_short Online Manifold Regularization by Dual Ascending Procedure
title_full Online Manifold Regularization by Dual Ascending Procedure
title_fullStr Online Manifold Regularization by Dual Ascending Procedure
title_full_unstemmed Online Manifold Regularization by Dual Ascending Procedure
title_sort online manifold regularization by dual ascending procedure
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approaches. An important conclusion is that our online MR algorithms can handle the settings where the target hypothesis is not fixed but drifts with the sequence of examples. We also recap and draw connections to earlier works. This paper paves a way to the design and analysis of online manifold regularization algorithms.
url http://dx.doi.org/10.1155/2013/838439
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