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NIPS
2008
15 years 4 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
ML
2011
ACM
308views Machine Learning» more  ML 2011»
14 years 9 months ago
Relational information gain
Abstract. Type Extension Trees (TET) have been recently introduced as an expressive representation language allowing to encode complex combinatorial features of relational entities...
Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andre...
129
Voted
BMCBI
2007
162views more  BMCBI 2007»
15 years 3 months ago
Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
Background: Genome-wide identification of specific oligonucleotides (oligos) is a computationallyintensive task and is a requirement for designing microarray probes, primers, and ...
Chun-Chi Liu, Chin-Chung Lin, Ker-Chau Li, Wen-Shy...
BMCBI
2007
226views more  BMCBI 2007»
15 years 3 months ago
MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans
Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of ...
Ting-Hua Huang, Bin Fan, Max F. Rothschild, Zhi-Li...
ICCV
2007
IEEE
16 years 5 months ago
A Scene Representation Based on Multi-Modal 2D and 3D Features
Visually extracted 2D and 3D information have their own advantages and disadvantages that complement each other. Therefore, it is important to be able to switch between the differ...
Emre Baseski, Nicolas Pugeault, Sinan Kalkan, Dirk...