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» Bayesian learning of joint distributions of objects
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KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 4 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
CORR
2004
Springer
191views Education» more  CORR 2004»
15 years 4 months ago
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
- This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence The research has b...
Pedro U. Lima, Luís M. M. Custódio
TNN
2010
234views Management» more  TNN 2010»
14 years 11 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
NECO
2011
14 years 11 months ago
Least Squares Estimation Without Priors or Supervision
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Martin Raphan, Eero P. Simoncelli
SIGIR
2005
ACM
15 years 10 months ago
A database centric view of semantic image annotation and retrieval
We introduce a new model for semantic annotation and retrieval from image databases. The new model is based on a probabilistic formulation that poses annotation and retrieval as c...
Gustavo Carneiro, Nuno Vasconcelos