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» Learning from sensor network data
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132
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NIPS
2007
15 years 4 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
112
Voted
ICAC
2007
IEEE
15 years 9 months ago
Autonomic Reactive Systems via Online Learning
— Reactive systems are those that maintain an ongoing interaction with their environment at a speed dictated by the latter. Examples of such systems include web servers, network ...
Sanjit A. Seshia
154
Voted
ECCB
2003
IEEE
15 years 8 months ago
Gene networks inference using dynamic Bayesian networks
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
127
Voted
RECOMB
2007
Springer
16 years 3 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
132
Voted
ML
2010
ACM
185views Machine Learning» more  ML 2010»
14 years 9 months ago
Learning to rank on graphs
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Shivani Agarwal