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» Learning a Generative Model for Structural Representations
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IJON
2011
169views more  IJON 2011»
13 years 2 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...
IDA
2009
Springer
14 years 2 months ago
Learning Natural Image Structure with a Horizontal Product Model
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
Urs Köster, Jussi T. Lindgren, Michael Gutman...
SIGDIAL
2010
13 years 5 months ago
Dialogue Act Modeling in a Complex Task-Oriented Domain
Classifying the dialogue act of a user utterance is a key functionality of a dialogue management system. This paper presents a data-driven dialogue act classifier that is learned ...
Kristy Elizabeth Boyer, Eun Y. Ha, Robert Phillips...
ICASSP
2011
IEEE
12 years 11 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke
IJCNN
2007
IEEE
14 years 1 months ago
Dynamic Pooling for the Combination of Forecasts generated using Multi Level Learning
— In this paper we provide experimental results and extensions to our previous theoretical findings concerning the combination of forecasts that have been diversified by three ...
Silvia Riedel, Bogdan Gabrys