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ICML
2010
IEEE
13 years 8 months ago
Multi-Task Learning of Gaussian Graphical Models
We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
Jean Honorio, Dimitris Samaras
ICANN
2003
Springer
14 years 28 days ago
Unsupervised Learning of a Kinematic Arm Model
Abstract. An abstract recurrent neural network trained by an unsupervised method is applied to the kinematic control of a robot arm. The network is a novel extension of the Neural ...
Heiko Hoffmann, Ralf Möller
DAGSTUHL
2007
13 years 9 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
IPSN
2010
Springer
13 years 5 months ago
i-MAC - a MAC that learns
Traffic patterns in manufacturing machines exhibit strong temporal correlations due to the underlying repetitive nature of their operations. A MAC protocol can potentially learn t...
Krishna Kant Chintalapudi
ICASSP
2011
IEEE
12 years 11 months ago
Dictionary learning of convolved signals
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...
Daniele Barchiesi, Mark D. Plumbley