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ICML
2004
IEEE
16 years 7 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
IJCNN
2006
IEEE
16 years 6 days ago
Knowledge Representation and Possible Worlds for Neural Networks
— The semantics of neural networks can be analyzed mathematically as a distributed system of knowledge and as systems of possible worlds expressed in the knowledge. Learning in a...
Michael J. Healy, Thomas P. Caudell
ICIP
2010
IEEE
15 years 3 months ago
Automatic target recognition based on simultaneous sparse representation
In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extr...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap...
LEGE
2004
103views Education» more  LEGE 2004»
15 years 7 months ago
Structuring and merging Distributed Content
A flexible approach for structuring and merging distributed learning object is presented. At the basis of this approach there is a formal representation of a learning object, call...
Luca Stefanutti, Dietrich Albert, Cord Hockemeyer
ATAL
2011
Springer
14 years 6 months ago
Metric learning for reinforcement learning agents
A key component of any reinforcement learning algorithm is the underlying representation used by the agent. While reinforcement learning (RL) agents have typically relied on hand-...
Matthew E. Taylor, Brian Kulis, Fei Sha