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SIAMJO
2011
13 years 3 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
TCOM
2011
130views more  TCOM 2011»
13 years 3 months ago
Indirect Reciprocity Game Modelling for Cooperation Stimulation in Cognitive Networks
—In cognitive networks, since nodes generally belong to different authorities and pursue different goals, they will not cooperate with others unless cooperation can improve their...
Yan Chen, K. J. Ray Liu
TIP
2011
123views more  TIP 2011»
13 years 3 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz
TMM
2011
169views more  TMM 2011»
13 years 3 months ago
Empowering Visual Categorization With the GPU
—Visual categorization is important to manage large collections of digital images and video, where textual metadata is often incomplete or simply unavailable. The bag-of-words mo...
Koen E. A. van de Sande, Theo Gevers, Cees G. M. S...
TNN
2011
200views more  TNN 2011»
13 years 3 months ago
Domain Adaptation via Transfer Component Analysis
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qi...
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