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ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
14 years 7 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König
ICASSP
2008
IEEE
15 years 4 months ago
Unsupervised learning of auditory filter banks using non-negative matrix factorisation
Non-negative matrix factorisation (NMF) is an unsupervised learning technique that decomposes a non-negative data matrix into a product of two lower rank non-negative matrices. Th...
Alexander Bertrand, Kris Demuynck, Veronique Stout...
ICML
2004
IEEE
15 years 3 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
BIOADIT
2004
Springer
15 years 1 months ago
Anatomy and Physiology of an Artificial Vision Matrix
We present a detailed account of the processing that occurs within a biologically-inspired model for visual homing. The Corner Gradient Snapshot Model (CGSM) initially presented in...
Andrew Vardy, Franz Oppacher
CIVR
2008
Springer
166views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Non-negative matrix factorisation for object class discovery and image auto-annotation
In information retrieval, sub-space techniques are usually used to reveal the latent semantic structure of a data-set by projecting it to a low dimensional space. Non-negative mat...
Jiayu Tang, Paul H. Lewis