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AIMSA
2008
Springer
15 years 8 months ago
Incorporating Learning in Grid-Based Randomized SAT Solving
Abstract. Computational Grids provide a widely distributed computing environment suitable for randomized SAT solving. This paper develops techniques for incorporating learning, kno...
Antti Eero Johannes Hyvärinen, Tommi A. Juntt...
P2P
2006
IEEE
101views Communications» more  P2P 2006»
15 years 7 months ago
Reinforcement Learning for Query-Oriented Routing Indices in Unstructured Peer-to-Peer Networks
The idea of building query-oriented routing indices has changed the way of improving routing efficiency from the basis as it can learn the content distribution during the query r...
Cong Shi, Shicong Meng, Yuanjie Liu, Dingyi Han, Y...
TSP
2010
14 years 8 months ago
Learning Gaussian tree models: analysis of error exponents and extremal structures
The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
SPEECH
2008
81views more  SPEECH 2008»
15 years 1 months ago
Supervised and unsupervised learning of multidimensionally varying non-native speech categories
The acquisition of novel phonetic categories is hypothesized to be affected by the distributional properties of the input, the relation of the new categories to the native phonolo...
Martijn Goudbeek, Anne Cutler, Roel Smits
117
Voted
IJAR
2010
130views more  IJAR 2010»
15 years 1 days ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki