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NIPS
2007
15 years 2 months ago
2007
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
87
Voted
NIPS
2007
15 years 2 months ago
2007
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...
86
Voted
NIPS
2007
15 years 2 months ago
2007
The control of high-dimensional, continuous, non-linear dynamical systems is a key problem in reinforcement learning and control. Local, trajectory-based methods, using techniques...
88
Voted
NIPS
2007
15 years 2 months ago
2007
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
130
Voted
NIPS
2004
15 years 2 months ago
2004
Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets of features. It has had a number of practical succ...