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NIPS
2001
13 years 9 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger
NECO
2002
117views more  NECO 2002»
13 years 7 months ago
Bayesian A* Tree Search with Expected O(N) Node Expansions: Applications to Road Tracking
Many perception, reasoning, and learning problems can be expressed as Bayesian inference. We point out that formulating a problem as Bayesian inference implies specifying a probabi...
James M. Coughlan, Alan L. Yuille
AGI
2011
12 years 11 months ago
Towards a General Vision System Based on Symbol-Relation Grammars and Bayesian Networks
Abstract. A novel approach to create a general vision system is presented. The proposed method is based on a visual grammar representation which is transformed to a Bayesian networ...
Elias Ruiz, Augusto Meléndez, Luis Enrique ...
UAI
2003
13 years 9 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
ICRA
2008
IEEE
208views Robotics» more  ICRA 2008»
14 years 2 months ago
Unsupervised body scheme learning through self-perception
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...
Jürgen Sturm, Christian Plagemann, Wolfram Bu...