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» Sparse Image Reconstruction using Sparse Priors
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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 4 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
CN
2007
141views more  CN 2007»
15 years 4 months ago
Identifying lossy links in wired/wireless networks by exploiting sparse characteristics
In this paper, we consider the problem of estimating link loss rates based on end-to-end path loss rates in order to identify lossy links on the network. We first derive a maximu...
Hyuk Lim, Jennifer C. Hou
CIMAGING
2009
192views Hardware» more  CIMAGING 2009»
15 years 5 months ago
Compressive coded aperture imaging
Nonlinear image reconstruction based upon sparse representations of images has recently received widespread attention with the emerging framework of compressed sensing (CS). This ...
Roummel F. Marcia, Zachary T. Harmany, Rebecca Wil...
MICCAI
2010
Springer
15 years 2 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
ICPR
2008
IEEE
15 years 10 months ago
Face super-resolution using 8-connected Markov Random Fields with embedded prior
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...