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ICASSP
2011
IEEE
14 years 9 months ago
Discriminative simplification of mixture models
Simplification of mixture models has recently emerged as an important issue in the field of statistical learning. The heavy computational demands of using large order models dro...
Yossi Bar-Yosef, Yuval Bistritz
CVPR
2004
IEEE
16 years 7 months ago
Super-Resolution through Neighbor Embedding
In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its highresolution counterpart using...
Hong Chang, Dit-Yan Yeung, Yimin Xiong
CVPR
2007
IEEE
16 years 7 months ago
Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
ICML
2004
IEEE
16 years 6 months ago
Solving cluster ensemble problems by bipartite graph partitioning
A critical problem in cluster ensemble research is how to combine multiple clusterings to yield a final superior clustering result. Leveraging advanced graph partitioning techniqu...
Xiaoli Zhang Fern, Carla E. Brodley
162
Voted
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 5 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney