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Manifold Alignment via Local Block Coordinates

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成果類型:
會議論文
作者:
Yang, Gelan*;Xu, Xue;Tu, Li
通訊作者:
Yang, Gelan
作者機構:
[Yang, Gelan; Tu, Li] Hunan City Univ, Dept Comp Sci, Yiyang, Peoples R China.
[Xu, Xue] Univ Sci & Technol China, Dept Automat, Hefei, Peoples R China.
通訊機構:
[Yang, Gelan] Hunan City Univ, Dept Comp Sci, Yiyang, Peoples R China.
語種:
英文
關鍵詞:
manifold alignment;local block coordinate;manifold constraint;Data matching
期刊:
WKDD: 2009 SECOND INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS
年:
2009
頁碼:
697-+
會議名稱:
2nd International Workshop on Knowledge Discovery Data Mining
會議時間:
JAN 23-25, 2009
會議地點:
Moscow, RUSSIA
會議主辦單位:
[Yang, Gelan;Tu, Li] Hunan City Univ, Dept Comp Sci, Yiyang, Peoples R China.^[Xu, Xue] Univ Sci & Technol China, Dept Automat, Hefei, Peoples R China.
會議贊助商:
Intelligent Informat Technol Applicat Res Assoc, Wuhan Univ, Sci & Technol Zhongnan Branch, Comp & Security
主編:
Luo, Q Gong, M
出版地:
10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
出版者:
IEEE COMPUTER SOC
ISBN:
978-0-7695-3543-2
基金類別:
Scientific Research Fund of Hunan Provincial Education Department [07C191, 08C195]; Scientific Research Fund of Hunan City University [07C017]; Scientific Research Fund of Hunan Provincial Construction Department [200609]
機構署名:
本校為第一且通訊機構
院系歸屬:
信息與電子工程學院
摘要:
We consider the problem of the correspondence leaning of two high-dimensional data sets via the manifold leaning techniques. It's convenient for us to find the shared latent structure of the high-dimensional data sets, if they can be aligned in a uniformed low-dimensional data space. A local affine technique to address this problem is present here. Our method preserves more geometrical knowledge of the high-dimensional data sets and can easily project the new test data into the aligned data space by the local transformation obtained during the training step. The effectiveness of our algorithm is validated by applying it to the problem of image sequences alignment.

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