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CVPR
2006
IEEE
14 years 11 months ago
Hierarchical Statistical Learning of Generic Parts of Object Structure
With the growing interest in object categorization various methods have emerged that perform well in this challenging task, yet are inherently limited to only a moderate number of...
Sanja Fidler, Gregor Berginc, Ales Leonardis
ICCV
2007
IEEE
14 years 3 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
TRECVID
2007
13 years 10 months ago
NII-ISM, Japan at TRECVID 2007: High Level Feature Extraction
This paper reports our experiments on the concept detection task of TRECVID 2007. In these experiments, we have addressed two approaches which are selecting and fusing features and...
Duy-Dinh Le, Shin'ichi Satoh, Tomoko Matsui
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 9 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
EUROPAR
2009
Springer
14 years 1 months ago
Two-Dimensional Matrix Partitioning for Parallel Computing on Heterogeneous Processors Based on Their Functional Performance Mod
Abstract. The functional performance model (FPM) of heterogeneous processors has proven to be more realistic than the traditional models because it integrates many important featur...
Alexey L. Lastovetsky, Ravi Reddy