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PVLDB
2010
135views more  PVLDB 2010»
14 years 4 months ago
QSkycube: Efficient Skycube Computation using Point-Based Space Partitioning
Skyline queries have gained considerable attention for multicriteria analysis of large-scale datasets. However, the skyline queries are known to return too many results for highdi...
Jongwuk Lee, Seung-won Hwang
CVPR
2007
IEEE
16 years 13 hour ago
Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
Jianhui Chen, Jieping Ye, Qi Li
ICCV
2005
IEEE
15 years 12 months ago
Neighborhood Preserving Embedding
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
ICML
2006
IEEE
15 years 10 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
COLT
2007
Springer
15 years 4 months ago
Minimax Bounds for Active Learning
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Rui Castro, Robert D. Nowak