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ICML
2006
IEEE
16 years 6 months ago
A new approach to data driven clustering
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Arik Azran, Zoubin Ghahramani
CISS
2008
IEEE
16 years 16 days ago
Distributed estimation in wireless sensor networks via variational message passing
Abstract – In this paper, a variational message passing framework is proposed for Markov random fields. Analogous to the traditional belief propagation algorithm, variational mes...
Yanbing Zhang, Huaiyu Dai
FOCS
2002
IEEE
15 years 11 months ago
Learning a Hidden Matching
We consider the problem of learning a matching (i.e., a graph in which all vertices have degree 0 or 1) in a model where the only allowed operation is to query whether a set of ve...
Noga Alon, Richard Beigel, Simon Kasif, Steven Rud...
NIPS
2003
15 years 7 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
CONNECTION
2006
101views more  CONNECTION 2006»
15 years 6 months ago
High capacity, small world associative memory models
Models of associative memory usually have full connectivity or if diluted, random symmetric connectivity. In contrast, biological neural systems have predominantly local, non-symm...
Neil Davey, Lee Calcraft, Rod Adams