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Challenges of big data analysis
Big Data bring new opportunities to modern society and challenges to data scientists. On the
one hand, Big Data hold great promises for discovering subtle population patterns and …
one hand, Big Data hold great promises for discovering subtle population patterns and …
A review of metabolomics approaches and their application in identifying causal pathways of childhood asthma
Because asthma is a disease that results from host-environment interactions, an approach
that allows assessment of the effect of the environment on the host is needed to understand …
that allows assessment of the effect of the environment on the host is needed to understand …
Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer
To identify common alleles associated with different histotypes of epithelial ovarian cancer
(EOC), we pooled data from multiple genome-wide genoty** projects totaling 25,509 EOC …
(EOC), we pooled data from multiple genome-wide genoty** projects totaling 25,509 EOC …
Process data analytics in the era of big data
For engineering systems where processes, units, and equipment are designed with clear
objectives and are usually operated under well‐controlled circumstances as designed …
objectives and are usually operated under well‐controlled circumstances as designed …
A Unified Framework for High-Dimensional Analysis of -Estimators with Decomposable Regularizers
SN Negahban, P Ravikumar, MJ Wainwright, B Yu - 2012 - projecteuclid.org
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable
Regularizers Page 1 Statistical Science 2012, Vol. 27, No. 4, 538–557 DOI: 10.1214/12-STS400 …
Regularizers Page 1 Statistical Science 2012, Vol. 27, No. 4, 538–557 DOI: 10.1214/12-STS400 …
Bayesian inference for structured additive regression models for large-scale problems with applications to medical imaging
P Schmidt - 2017 - edoc.ub.uni-muenchen.de
In der angewandten Statistik können Regressionsmodelle mit hochdimensionalen
Koeffizienten auftreten, die sich nicht mit gewöhnlichen Computersystemen schätzen …
Koeffizienten auftreten, die sich nicht mit gewöhnlichen Computersystemen schätzen …
Statistical challenges of high-dimensional data
IM Johnstone, DM Titterington - … transactions of the …, 2009 - royalsocietypublishing.org
Modern applications of statistical theory and methods can involve extremely large datasets,
often with huge numbers of measurements on each of a comparatively small number of …
often with huge numbers of measurements on each of a comparatively small number of …
A unified framework for high-dimensional analysis of -estimators with decomposable regularizers
The estimation of high-dimensional parametric models requires imposing some structure on
the models, for instance that they be sparse, or that matrix structured parameters have low …
the models, for instance that they be sparse, or that matrix structured parameters have low …
Exploring massive, genome scale datasets with the GenometriCorr package
We have created a statistically grounded tool for determining the correlation of genomewide
data with other datasets or known biological features, intended to guide biological …
data with other datasets or known biological features, intended to guide biological …
A new link between diabetes and cancer: enhanced WNT/β-catenin signaling by high glucose
Extensive epidemiological studies suggest that the diabetic population is at higher risk of
site-specific cancers. The diabetes–cancer link has been hypothesized to rely on various …
site-specific cancers. The diabetes–cancer link has been hypothesized to rely on various …