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» GSML: A Unified Framework for Sparse Metric Learning
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ECCV
2006
Springer
14 years 6 months ago
Conditional Infomax Learning: An Integrated Framework for Feature Extraction and Fusion
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Dahua Lin, Xiaoou Tang
BMCBI
2010
182views more  BMCBI 2010»
13 years 4 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
CVPR
2011
IEEE
13 years 1 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
CVPR
2009
IEEE
14 years 1 months ago
Visual loop closing using multi-resolution SIFT grids in metric-topological SLAM
We present an image-based Simultaneous Localization and Mapping (SLAM) framework with online, appearanceonly loop closing. We adopt a layered approach with metric maps over small ...
Vivek Pradeep, Gérard G. Medioni, James Wei...
SIGMOD
2004
ACM
262views Database» more  SIGMOD 2004»
14 years 4 months ago
The Next Database Revolution
Database system architectures are undergoing revolutionary changes. Most importantly, algorithms and data are being unified by integrating programming languages with the database ...
Jim Gray