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NIPS
2008
15 years 4 months ago
Spectral Clustering with Perturbed Data
Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
Ling Huang, Donghui Yan, Michael I. Jordan, Nina T...
CGF
2008
101views more  CGF 2008»
15 years 3 months ago
Spectral Conformal Parameterization
We present a spectral approach to automatically and efficiently obtain discrete free-boundary conformal parameterizations of triangle mesh patches, without the common artifacts du...
Patrick Mullen, Yiying Tong, Pierre Alliez, Mathie...
SPAA
1997
ACM
15 years 7 months ago
HARP: A Fast Spectral Partitioner
- Partitioning unstructured graphs is central to the parallel solution of computational science and engineering problems. Spectral partitioners, such recursive spectral bisection (...
Horst D. Simon, Andrew Sohn, Rupak Biswas
CVPR
2009
IEEE
16 years 10 months ago
Constrained Clustering via Spectral Regularization
We propose a novel framework for constrained spectral clustering with pairwise constraints which specify whether two objects belong to the same cluster or not. Unlike previous m...
Zhenguo Li (The Chinese University of Hong Kong), ...
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DCC
2007
IEEE
16 years 3 months ago
Spectral Predictors
Many scientific, imaging, and geospatial applications produce large high-precision scalar fields sampled on a regular grid. Lossless compression of such data is commonly done usin...
Lorenzo Ibarria, Peter Lindstrom, Jarek Rossignac