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» Spectral clustering based on matrix perturbation theory
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NIPS
2004
13 years 8 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...
ISBI
2011
IEEE
12 years 11 months ago
3D elastic registration improves HARDI-derived fiber alignment and automated tract clustering
High angular resolution diffusion imaging (HARDI) allows population studies of fiber integrity and connectivity. Tractography can extract individual fibers. For group studies, fib...
Yan Jin, Yonggang Shi, Neda Jahanshad, Iman Aganj,...
SIAMJO
2002
99views more  SIAMJO 2002»
13 years 7 months ago
Active Sets, Nonsmoothness, and Sensitivity
Nonsmoothness pervades optimization, but the way it typically arises is highly structured. Nonsmooth behavior of an objective function is usually associated, locally, with an activ...
A. S. Lewis
STOC
2004
ACM
145views Algorithms» more  STOC 2004»
14 years 7 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
NIPS
2007
13 years 8 months ago
Discriminative K-means for Clustering
We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...
Jieping Ye, Zheng Zhao, Mingrui Wu