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» On the Use of Evidence in Neural Networks
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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 6 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
TAP
2008
Springer
102views Hardware» more  TAP 2008»
13 years 5 months ago
Visualizing graphs in three dimensions
It has been known for some time that larger graphs can be interpreted if laid out in 3D and displayed with stereo and/or motion depth cues to support spatial perception. However, ...
Colin Ware, Peter Mitchell
BMCBI
2006
123views more  BMCBI 2006»
13 years 5 months ago
Computational models with thermodynamic and composition features improve siRNA design
Background: Small interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large fun...
Svetlana A. Shabalina, Alexey N. Spiridonov, Aleks...
ICML
1996
IEEE
14 years 6 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore