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» Theoretical and empirical results for recovery from multiple...
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CVPR
2012
IEEE
11 years 9 months ago
Unsupervised metric fusion by cross diffusion
Metric learning is a fundamental problem in computer vision. Different features and algorithms may tackle a problem from different angles, and thus often provide complementary inf...
Bo Wang, Jiayan Jiang, Wei Wang 0028, Zhi-Hua Zhou...
SIGIR
2010
ACM
13 years 7 months ago
Optimal meta search results clustering
By analogy with merging documents rankings, the outputs from multiple search results clustering algorithms can be combined into a single output. In this paper we study the feasibi...
Claudio Carpineto, Giovanni Romano
TSP
2008
151views more  TSP 2008»
13 years 7 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
SCAM
2005
IEEE
14 years 28 days ago
Measuring the Impact of Friends on the Internal Attributes of Software Systems
Differing views have been expressed on the appropriateness of the friend construct in the design and implementation of object-oriented software in C++. However, little empirical a...
Michael English, Jim Buckley, Tony Cahill, Kristia...
ECCV
2006
Springer
13 years 11 months ago
A Batch Algorithm for Implicit Non-rigid Shape and Motion Recovery
The recovery of 3D shape and camera motion for non-rigid scenes from single-camera video footage is a very important problem in computer vision. The low-rank shape model consists ...
Adrien Bartoli, Søren I. Olsen