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» Distributed parameter estimation with selective cooperation
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ML
2002
ACM
178views Machine Learning» more  ML 2002»
13 years 9 months ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
AUTONOMICS
2009
ACM
14 years 4 months ago
Sensor Selection for IT Infrastructure Monitoring
Supervisory control is the main means to assure a high level performance and availability of large IT infrastructures. Applied control theory is used in physical and virtualization...
Gergely János Paljak, Imre Kocsis, Zolt&aac...
ICDM
2006
IEEE
226views Data Mining» more  ICDM 2006»
14 years 3 months ago
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Jing Gao, Pang-Ning Tan
DSP
2008
13 years 9 months ago
Empirical Bayes linear regression with unknown model order
We study maximum a posteriori probability model order selection for linear regression models, assuming Gaussian distributed noise and coefficient vectors. For the same data model,...
Yngve Selén, Erik G. Larsson
WSC
2004
13 years 11 months ago
Adaptive Control Variates
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
Sujin Kim, Shane G. Henderson