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» Learn .MT: A New Approach to Incremental Learning
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ICPR
2008
IEEE
16 years 1 months ago
Improving Bayesian Network parameter learning using constraints
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
Cassio Polpo de Campos, Qiang Ji
ATAL
2010
Springer
15 years 7 months ago
Learning context conditions for BDI plan selection
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
EUROCOLT
1995
Springer
15 years 10 months ago
The structure of intrinsic complexity of learning
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
Sanjay Jain, Arun Sharma
GLOBECOM
2010
IEEE
15 years 4 months ago
Reinforcement Learning for Link Adaptation in MIMO-OFDM Wireless Systems
Machine learning algorithms have recently attracted much interest for effective link adaptation due to their flexibility and ability to capture more environmental effects implicitl...
Sungho Yun, Constantine Caramanis
TEC
2012
197views Formal Methods» more  TEC 2012»
13 years 9 months ago
Improving Generalization Performance in Co-Evolutionary Learning
Recently, the generalization framework in co-evolutionary learning has been theoretically formulated and demonstrated in the context of game-playing. Generalization performance of...
Siang Yew Chong, Peter Tino, Day Chyi Ku, Xin Yao