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ICCV
2003
IEEE
16 years 7 months ago
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Lior Wolf, Amnon Shashua
ICIP
2003
IEEE
16 years 6 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...
INFOCOM
2007
IEEE
15 years 11 months ago
Landmark Selection and Greedy Landmark-Descent Routing for Sensor Networks
—We study the problem of landmark selection for landmark-based routing in a network of fixed wireless communication nodes. We present a distributed landmark selection algorithm ...
An Nguyen, Nikola Milosavljevic, Qing Fang, Jie Ga...
158
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OOPSLA
2001
Springer
15 years 9 months ago
Regression Test Selection for Java Software
Regression testing is applied to modified software to provide confidence that the changed parts behave as intended and that the unchanged parts have not been adversely affected ...
Mary Jean Harrold, James A. Jones, Tongyu Li, Dong...
KDD
2010
ACM
197views Data Mining» more  KDD 2010»
15 years 3 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu