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» Local Dimensionality Reduction
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TOG
2002
125views more  TOG 2002»
15 years 3 months ago
Perspective shadow maps
Shadow maps are probably the most widely used means for the generation of shadows, despite their well known aliasing problems. In this paper we introduce perspective shadow maps, ...
Marc Stamminger, George Drettakis
110
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PR
2007
88views more  PR 2007»
15 years 2 months ago
Robust kernel Isomap
Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
Heeyoul Choi, Seungjin Choi
PVLDB
2008
93views more  PVLDB 2008»
15 years 2 months ago
Querying and mining of time series data: experimental comparison of representations and distance measures
The last decade has witnessed a tremendous growths of interests in applications that deal with querying and mining of time series data. Numerous representation methods for dimensi...
Hui Ding, Goce Trajcevski, Peter Scheuermann, Xiao...
133
Voted
CIKM
2010
Springer
15 years 2 months ago
Visualization and clustering of crowd video content in MPCA subspace
This paper presents a novel approach for the visualization and clustering of crowd video contents by using multilinear principal component analysis (MPCA). In contrast to feature-...
Haiping Lu, How-Lung Eng, Myo Thida, Konstantinos ...
CORR
2010
Springer
189views Education» more  CORR 2010»
15 years 1 months ago
Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
Huan Xu, Constantine Caramanis, Sujay Sanghavi