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» Unsupervised Learning Using MML
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CVPR
2000
IEEE
14 years 10 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
ICML
2007
IEEE
14 years 9 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
ICML
2005
IEEE
14 years 9 months ago
Multi-way distributional clustering via pairwise interactions
We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...
Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
BIOADIT
2006
Springer
14 years 12 days ago
Attractor Memory with Self-organizing Input
We propose a neural network based autoassociative memory system for unsupervised learning. This system is intended to be an example of how a general information processing architec...
Christopher Johansson, Anders Lansner
EELC
2006
128views Languages» more  EELC 2006»
14 years 10 days ago
Evolving Distributed Representations for Language with Self-Organizing Maps
We present a neural-competitive learning model of language evolution in which several symbol sequences compete to signify a given propositional meaning. Both symbol sequences and p...
Simon D. Levy, Simon Kirby