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» Computability of Models for Sequence Assembly
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COLT
1992
Springer
15 years 10 months ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi
NIPS
2008
15 years 8 months ago
The Recurrent Temporal Restricted Boltzmann Machine
The Temporal Restricted Boltzmann Machine (TRBM) is a probabilistic model for sequences that is able to successfully model (i.e., generate nice-looking samples of) several very hi...
Ilya Sutskever, Geoffrey E. Hinton, Graham W. Tayl...
ISMB
2004
15 years 7 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
BMCBI
2010
113views more  BMCBI 2010»
15 years 6 months ago
Unifying generative and discriminative learning principles
Background: The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of differe...
Jens Keilwagen, Jan Grau, Stefan Posch, Marc Stric...
CVPR
2008
IEEE
16 years 8 months ago
Extracting a fluid dynamic texture and the background from video
Given the video of a still background occluded by a fluid dynamic texture (FDT), this paper addresses the problem of separating the video sequence into its two constituent layers....
Bernard Ghanem, Narendra Ahuja