A high-bias, low-variance introduction to machine learning for physicists
Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …
research and application. The purpose of this review is to provide an introduction to the core …
Multi-omic and multi-view clustering algorithms: review and cancer benchmark
N Rappoport, R Shamir - Nucleic acids research, 2018 - academic.oup.com
Recent high throughput experimental methods have been used to collect large biomedical
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …
Predicting reaction performance in C–N cross-coupling using machine learning
Machine learning methods are becoming integral to scientific inquiry in numerous
disciplines. We demonstrated that machine learning can be used to predict the performance …
disciplines. We demonstrated that machine learning can be used to predict the performance …
[图书][B] Introduction to statistical process control
P Qiu - 2013 - books.google.com
A major tool for quality control and management, statistical process control (SPC) monitors
sequential processes, such as production lines and Internet traffic, to ensure that they work …
sequential processes, such as production lines and Internet traffic, to ensure that they work …
[图书][B] Mathematical statistics: basic ideas and selected topics, volumes I-II package
This package includes both Mathematical Statistics: Basic Ideas and Selected Topics,
Volume I, Second Edition, as well as Mathematical Statistics: Basic Ideas and Selected …
Volume I, Second Edition, as well as Mathematical Statistics: Basic Ideas and Selected …
[HTML][HTML] A selective overview of variable selection in high dimensional feature space
High dimensional statistical problems arise from diverse fields of scientific research and
technological development. Variable selection plays a pivotal role in contemporary statistical …
technological development. Variable selection plays a pivotal role in contemporary statistical …
Estimation of (near) low-rank matrices with noise and high-dimensional scaling
S Negahban, MJ Wainwright - 2011 - projecteuclid.org
Estimation of (near) low-rank matrices with noise and high-dimensional scaling Page 1 The
Annals of Statistics 2011, Vol. 39, No. 2, 1069–1097 DOI: 10.1214/10-AOS850 © Institute of …
Annals of Statistics 2011, Vol. 39, No. 2, 1069–1097 DOI: 10.1214/10-AOS850 © Institute of …
Microbiome multi-omics network analysis: statistical considerations, limitations, and opportunities
The advent of large-scale microbiome studies affords newfound analytical opportunities to
understand how these communities of microbes operate and relate to their environment …
understand how these communities of microbes operate and relate to their environment …
A unified approach to model selection and sparse recovery using regularized least squares
Abstract Model selection and sparse recovery are two important problems for which many
regularization methods have been proposed. We study the properties of regularization …
regularization methods have been proposed. We study the properties of regularization …
[HTML][HTML] Adaptive robust variable selection
Heavy-tailed high-dimensional data are commonly encountered in various scientific fields
and pose great challenges to modern statistical analysis. A natural procedure to address this …
and pose great challenges to modern statistical analysis. A natural procedure to address this …