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» Learning a Generative Model for Structural Representations
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NIPS
2008
13 years 9 months ago
Structure Learning in Human Sequential Decision-Making
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Daniel Acuña, Paul R. Schrater
JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
CVPR
2011
IEEE
13 years 5 months ago
Learning Better Image Representations Using 'Flobject Analysis'
Unsupervised learning can be used to extract image representations that are useful for various and diverse vision tasks. After noticing that most biological vision systems for int...
Inmar Givoni, Patrick Li, Brendan Frey
ISMB
1993
13 years 8 months ago
Representation for Discovery of Protein Motifs
There are several dimensions and levels of complexity in which information on protein motifs may be available. For example, onedimensional sequence motifs may be associated with s...
Darrell Conklin, Suzanne Fortier, Janice I. Glasgo...
ICDAR
1997
IEEE
13 years 11 months ago
Modeling Documents for Structure Recognition Using Generalized N-Grams
In this paper we present and discuss a novel approach to modeling logical structures of documents, based on a statistical representation of patterns in a document class. An effic...
Rolf Brugger, Abdel Wahab Zramdini, Rolf Ingold