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132
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COLT
2006
Springer
15 years 7 months ago
Learning Rational Stochastic Languages
Given a finite set of words w1, . . . , wn independently drawn according to a fixed unknown distribution law P called a stochastic language, an usual goal in Grammatical Inference ...
François Denis, Yann Esposito, Amaury Habra...
125
Voted
IJCAI
2007
15 years 5 months ago
Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition
Most existing sketch understanding systems require a closed domain to achieve recognition. This paper describes an incremental learning technique for opendomain recognition. Our s...
Andrew M. Lovett, Morteza Dehghani, Kenneth D. For...
134
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UAI
1997
15 years 4 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
122
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SIGGRAPH
2010
ACM
15 years 8 months ago
Vector solid textures
In this paper, we introduce a compact random-access vector representation for solid textures made of intermixed regions with relatively smooth internal color variations. It is fea...
Lvdi Wang, Kun Zhou, Yizhou Yu, Baining Guo
FLAIRS
2004
15 years 5 months ago
A Functional and Behavioral Knowledge-based Implementation for Intelligent Sensors/Actuators
As the complexity of industrial processes increases, it requires the use of intelligent sensors or actuators (known as Intelligent Instruments) to allow for more comprehensive and...
Richard Dapoigny, Patrick Barlatier, Laurent Foull...