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» Learning Structured Models for Phone Recognition
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ATAL
2006
Springer
13 years 10 months ago
Learning executable agent behaviors from observation
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
15 years 1 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
CG
1999
Springer
13 years 6 months ago
There is more to context than location
Context is a key issue in interaction between human and computer, describing the surrounding facts that add meaning. In mobile computing research published the parameter location ...
Albrecht Schmidt, Michael Beigl, Hans-Werner Gelle...
COLT
1994
Springer
13 years 10 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
ANNPR
2008
Springer
13 years 8 months ago
Supervised Incremental Learning with the Fuzzy ARTMAP Neural Network
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
Jean-François Connolly, Eric Granger, Rober...