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COLT
2008
Springer
15 years 6 months ago
Model Selection and Stability in k-means Clustering
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
Ohad Shamir, Naftali Tishby
170
Voted
JMLR
2006
92views more  JMLR 2006»
15 years 5 months ago
Linear Programs for Hypotheses Selection in Probabilistic Inference Models
We consider an optimization problem in probabilistic inference: Given n hypotheses Hj, m possible observations Ok, their conditional probabilities pk j, and a particular Ok, selec...
Anders Bergkvist, Peter Damaschke, Marcel Lüt...
TKDE
1998
163views more  TKDE 1998»
15 years 4 months ago
A Highly Effective Partition Selection Policy for Object Database Garbage Collection
—We investigate methods to improve the performance of algorithms for automatic storage reclamation of object databases. These algorithms are based on a technique called partition...
Jonathan E. Cook, Alexander L. Wolf, Benjamin G. Z...
SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
16 years 5 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang
PSIVT
2007
Springer
126views Multimedia» more  PSIVT 2007»
15 years 11 months ago
Segmentation of Scanned Insect Footprints Using ART2 for Threshold Selection
Abstract. In a process of insect footprint recognition, footprint segments need to be extracted from scanned insect footprints in order to find out appropriate features for classi...
Bok-Suk Shin, Eui-Young Cha, Young Woon Woo, Reinh...