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» A New Algorithm for Answer Set Computation
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AI
2010
Springer
15 years 6 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
BMCBI
2008
104views more  BMCBI 2008»
15 years 6 months ago
ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS)
Background: Genome survey sequences (GSS) offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive region...
Thomas D. Otto, Leonardo H. F. Gomes, Marcelo Alve...
STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 10 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
ECML
2007
Springer
16 years 15 days ago
Learning Balls of Strings with Correction Queries
When facing the question of learning languages in realistic settings, one has to tackle several problems that do not admit simple solutions. On the one hand, languages are usually...
Leonor Becerra-Bonache, Colin de la Higuera, Jean-...
JMLR
2010
106views more  JMLR 2010»
15 years 1 months ago
Why Does Unsupervised Pre-training Help Deep Learning?
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...