This review article gives a high-level overview of the approaches across different scales of organization and levels of abstraction. The studies covered in this paper include …
Meeting the Paris Agreement's climate targets necessitates better knowledge about which climate policies work in reducing emissions at the necessary scale. We provide a global …
Data-driven discovery of dynamics via machine learning is pushing the frontiers of modelling and control efforts, providing a tremendous opportunity to extend the reach of model …
Lung cancer is one of the deadliest cancers in the world. Two of the most common subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), have drastically …
P Sur, EJ Candès - Proceedings of the National Academy of …, 2019 - National Acad Sciences
Students in statistics or data science usually learn early on that when the sample size n is large relative to the number of variables p, fitting a logistic model by the method of maximum …
Over the last decade or so, Approximate Message Passing (AMP) algorithms have become extremely popular in various structured high-dimensional statistical problems. Although the …
Praise for the first edition:"[This book] succeeds singularly at providing a structured introduction to this active field of research.… it is arguably the most accessible overview yet …
Z Zhou, G Hooker, F Wang - Proceedings of the 27th ACM SIGKDD …, 2021 - dl.acm.org
An increasing number of machine learning models have been deployed in domains with high stakes such as finance and healthcare. Despite their superior performances, many …
Regularized regression problems are ubiquitous in statistical modeling, signal processing, and machine learning. Sparse regression, in particular, has been instrumental in scientific …