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ICML
2005
IEEE
15 years 10 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
68
Voted
ICML
2010
IEEE
14 years 10 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
ICML
2005
IEEE
15 years 10 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
GECCO
2008
Springer
184views Optimization» more  GECCO 2008»
14 years 10 months ago
Evolutionary facial feature selection
With the growing number of acquired physiological and behavioral biometric samples, biometric data sets are experiencing tremendous growth. As database sizes increase, exhaustive ...
Aaron K. Baughman
BMCBI
2004
126views more  BMCBI 2004»
14 years 9 months ago
A probabilistic model for the evolution of RNA structure
Background: For the purposes of finding and aligning noncoding RNA gene- and cis-regulatory elements in multiple-genome datasets, it is useful to be able to derive multi-sequence ...
Ian Holmes