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BMCBI
2011
12 years 11 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
ICML
2008
IEEE
14 years 8 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
ASC
2006
13 years 8 months ago
Speeding up the learning of equivalence classes of bayesian network structures
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...
Rónán Daly, Qiang Shen, J. Stuart Ai...
CII
2006
95views more  CII 2006»
13 years 7 months ago
A neuro-fuzzy monitoring system: Application to flexible production systems
The multiple reconfiguration and the complexity of the modern production system lead to design intelligent monitoring aid systems. Accordingly, the use of neurofuzzy technics seem...
N. Palluat, Daniel I. Racoceanu, Noureddine Zerhou...
COLT
2005
Springer
14 years 1 months ago
Learning Convex Combinations of Continuously Parameterized Basic Kernels
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...