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» Feature Selection in Clustering Problems
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ESWA
2007
100views more  ESWA 2007»
13 years 8 months ago
Using memetic algorithms with guided local search to solve assembly sequence planning
The goal of assembly planning consists in generating feasible sequences to assemble a product and selecting an efficient assembly sequence from which related constraint factors su...
Hwai-En Tseng, Wen-Pai Wang, Hsun-Yi Shih
JMLR
2008
169views more  JMLR 2008»
13 years 8 months ago
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Jieping Ye, Shuiwang Ji, Jianhui Chen
CVPR
2003
IEEE
14 years 11 months ago
Generalized Principal Component Analysis (GPCA)
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...
René Vidal, Shankar Sastry, Yi Ma
WWW
2005
ACM
14 years 9 months ago
Three-level caching for efficient query processing in large Web search engines
Large web search engines have to answer thousands of queries per second with interactive response times. Due to the sizes of the data sets involved, often in the range of multiple...
Xiaohui Long, Torsten Suel
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
14 years 9 months ago
TANGENT: a novel, 'Surprise me', recommendation algorithm
Most of recommender systems try to find items that are most relevant to the older choices of a given user. Here we focus on the "surprise me" query: A user may be bored ...
Kensuke Onuma, Hanghang Tong, Christos Faloutsos