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» Unsupervised Learning with Permuted Data
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CVPR
2010
IEEE
14 years 10 months ago
Deconvolutional networks
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylo...
ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
14 years 7 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang
SDM
2004
SIAM
189views Data Mining» more  SDM 2004»
14 years 11 months ago
An Abstract Weighting Framework for Clustering Algorithms
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
Richard Nock, Frank Nielsen
SADM
2010
194views more  SADM 2010»
14 years 8 months ago
Seriation and matrix reordering methods: An historical overview
: Seriation is an exploratory combinatorial data analysis technique to reorder objects into a sequence along a one-dimensional continuum so that it best reveals regularity and patt...
Innar Liiv
83
Voted
ICML
2007
IEEE
15 years 10 months ago
Maximum margin clustering made practical
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
Kai Zhang, Ivor W. Tsang, James T. Kwok