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» Structure learning of Bayesian networks using constraints
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BC
2002
193views more  BC 2002»
15 years 4 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
PRICAI
2004
Springer
15 years 10 months ago
An Anytime Algorithm for Interpreting Arguments
Abstract. The problem of interpreting Natural Language (NL) discourse is generally of exponential complexity. However, since interactions with users must be conducted in real time,...
Sarah George, Ingrid Zukerman, Michael Niemann
ICDAR
2009
IEEE
15 years 11 months ago
Isolated Handwritten Farsi Numerals Recognition Using Sparse and Over-Complete Representations
A new isolated handwritten Farsi numeral recognition algorithm is proposed in this paper, which exploits the sparse and over-complete structure from the handwritten Farsi numeral ...
Wumo Pan, Tien D. Bui, Ching Y. Suen
BMCBI
2010
179views more  BMCBI 2010»
15 years 4 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
AI
2008
Springer
15 years 4 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...