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SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
16 years 4 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICPR
2008
IEEE
16 years 5 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
TCSV
2010
14 years 11 months ago
Face and Human Gait Recognition Using Image-to-Class Distance
We propose a new distance measure for face recognition and human gait recognition. Each probe image (a face image or an average human silhouette image) is represented as a set of ...
Yi Huang, Dong Xu, Tat-Jen Cham
EDBT
2006
ACM
191views Database» more  EDBT 2006»
16 years 4 months ago
Distributed Spatial Clustering in Sensor Networks
Abstract. Sensor networks monitor physical phenomena over large geographic regions. Scientists can gain valuable insight into these phenomena, if they understand the underlying dat...
Anand Meka, Ambuj K. Singh
CVPR
2009
IEEE
16 years 11 months ago
Unsupervised Maximum Margin Feature Selection with Manifold Regularization
Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature s...
Bin Zhao, James Tin-Yau Kwok, Fei Wang, Changshui ...