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» Constrained Clustering via Spectral Regularization
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CVPR
2009
IEEE
14 years 11 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), ...
JMLR
2012
11 years 6 months ago
Primal-Dual methods for sparse constrained matrix completion
We develop scalable algorithms for regular and non-negative matrix completion. In particular, we base the methods on trace-norm regularization that induces a low rank predicted ma...
Yu Xin, Tommi Jaakkola
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
13 years 10 months ago
Discrete Regularization for Perceptual Image Segmentation via Semi-Supervised Learning and Optimal Control
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Hongwei Zheng, Olaf Hellwich
CIKM
2007
Springer
13 years 10 months ago
Regularized locality preserving indexing via spectral regression
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He, Wei Vivian Zhang, Jiawei Han
CVPR
2012
IEEE
11 years 6 months ago
Higher order motion models and spectral clustering
Motion segmentation based on point trajectories can integrate information of a whole video shot to detect and separate moving objects. Commonly, similarities are defined between ...
Peter Ochs, Thomas Brox