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» Learning locally minimax optimal Bayesian networks
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BMCBI
2006
239views more  BMCBI 2006»
14 years 9 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
IJON
2006
138views more  IJON 2006»
14 years 9 months ago
Time-series prediction using a local linear wavelet neural network
A local linear wavelet neural network (LLWNN) is presented in this paper. The difference of the network with conventional wavelet neural network (WNN) is that the connection weigh...
Yuehui Chen, Bo Yang, Jiwen Dong
90
Voted
NIPS
1994
14 years 10 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
BMCBI
2007
136views more  BMCBI 2007»
14 years 9 months ago
Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...
Xiaoyu Chen, Mathieu Blanchette
87
Voted
UAI
2008
14 years 11 months ago
Observation Subset Selection as Local Compilation of Performance Profiles
Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
Yan Radovilsky, Solomon Eyal Shimony