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» EM in High Dimensional Spaces
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95
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TSP
2008
151views more  TSP 2008»
14 years 10 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
TSMC
1998
93views more  TSMC 1998»
14 years 10 months ago
Toward a completely automatic neural-network-based human chromosome analysis
Abstract—The application of neural networks (NN’s) to automatic analysis of chromosome images is investigated in this paper. All aspects of the analysis, namely segmentation, f...
Boaz Lerner
93
Voted
PAMI
2010
168views more  PAMI 2010»
14 years 8 months ago
Surface-from-Gradients without Discrete Integrability Enforcement: A Gaussian Kernel Approach
—Representative surface reconstruction algorithms taking a gradient field as input enforces the integrability constraint in a discrete manner. While enforcing integrability allo...
Heung-Sun Ng, Tai-Pang Wu, Chi-Keung Tang
BMCBI
2010
131views more  BMCBI 2010»
14 years 5 months ago
Dynamics based alignment of proteins: an alternative approach to quantify dynamic similarity
Background: The dynamic motions of many proteins are central to their function. It therefore follows that the dynamic requirements of a protein are evolutionary constrained. In or...
Márton Münz, Rune B. Lyngsø, Jo...
112
Voted
ICDE
2012
IEEE
202views Database» more  ICDE 2012»
13 years 20 days ago
Differentially Private Spatial Decompositions
— Differential privacy has recently emerged as the de facto standard for private data release. This makes it possible to provide strong theoretical guarantees on the privacy and ...
Graham Cormode, Cecilia M. Procopiuc, Divesh Sriva...