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UAI
1997
15 years 7 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
CORR
2007
Springer
164views Education» more  CORR 2007»
15 years 6 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach
ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
15 years 5 months ago
Learning and planning high-dimensional physical trajectories via structured Lagrangians
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi
TIP
2010
155views more  TIP 2010»
15 years 4 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
BMVC
2010
15 years 4 months ago
Manifold Learning for Multi-Modal Image Registration
The standard approach to multi-modal registration is to apply sophisticated similarity metrics such as mutual information. The disadvantage of these measures, in contrast to simpl...
Christian Wachinger, Nassir Navab