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Regression Shrinkage and Selection Via the Lasso
SUMMARY We propose a new method for estimation in linear models. The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients b...
Genetic algorithms in search, optimization, and machine learning
From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both st...
A new look at the statistical model identification
The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not a...
Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm
Summary A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone ...
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. ...
UCSF Chimera—A visualization system for exploratory research and analysis
Abstract The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic se...
Particle swarm optimization
The base isolation design usually used the historical well-known earthquake records as an input ground motion. Through the adjustment on each variables of the structure system, ...
Going deeper with convolutions
We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Sca...