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» Adversarial Sequence Prediction
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106
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STACS
1999
Springer
15 years 5 months ago
Costs of General Purpose Learning
Leo Harrington surprisingly constructed a machine which can learn any computable function f according to the following criterion (called Bc∗ -identification). His machine, on t...
John Case, Keh-Jiann Chen, Sanjay Jain
112
Voted
ALENEX
2010
163views Algorithms» more  ALENEX 2010»
15 years 2 months ago
Succinct Trees in Practice
We implement and compare the major current techniques for representing general trees in succinct form. This is important because a general tree of n nodes is usually represented i...
Diego Arroyuelo, Rodrigo Cánovas, Gonzalo N...
90
Voted
ISMB
2004
15 years 2 months ago
Exploiting conserved structure for faster annotation of non-coding RNAs without loss of accuracy
Motivation: Non-coding RNAs (ncRNAs)--functional RNA molecules not coding for proteins--are grouped into hundreds of families of homologs. To find new members of an ncRNA gene fam...
Zasha Weinberg, Walter L. Ruzzo
ALMOB
2008
160views more  ALMOB 2008»
15 years 25 days ago
Syntenator: Multiple gene order alignments with a gene-specific scoring function
Background: Identification of homologous regions or conserved syntenies across genomes is one crucial step in comparative genomics. This task is usually performed by genome alignm...
Christian Rödelsperger, Christoph Dieterich
BMCBI
2010
229views more  BMCBI 2010»
15 years 25 days ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck