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» Learning How to Propagate Using Random Probing
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ICCV
2009
IEEE
13 years 6 months ago
On optimizing subspaces for face recognition
We propose a subspace learning algorithm for face recognition by directly optimizing recognition performance scores. Our approach is motivated by the following observations: 1) Di...
Jilin Tu, Xiaoming Liu, Peter Henry Tu
KDD
2008
ACM
121views Data Mining» more  KDD 2008»
14 years 9 months ago
Reconstructing chemical reaction networks: data mining meets system identification
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Yong Ju Cho, Naren Ramakrishnan, Yang Cao
CORR
2008
Springer
98views Education» more  CORR 2008»
13 years 9 months ago
Information Acquisition and Exploitation in Multichannel Wireless Networks
A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by ...
Sudipto Guha, Kamesh Munagala, Saswati Sarkar
ICMCS
2009
IEEE
131views Multimedia» more  ICMCS 2009»
13 years 6 months ago
Web image mining using concept sensitive Markov stationary features
With the explosive growth of web resources, how to mine semantically relevant images efficiently becomes a challenging and necessary task. In this paper, we propose a concept sens...
Chunjie Zhang, Jing Liu, Hanqing Lu, Songde Ma
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
13 years 10 months ago
Fast Online SVD Revisions for Lightweight Recommender Systems
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
Matthew Brand