Add to ORKGWe give an overview of random matrix theory (RMT) with the objective of highlighting the results and concepts that have a growing impact in the formulation and inference of statistical models and methodologies. This paper focuses on a number of application areas especially within the field of high-dimensional statistics and describes how the development of the theory and practice in high-dimensional statistical inference has been influenced by the corresponding developments in the field of RMT. © 2014 Elsevier B.V
We review some recent developments in random matrix theory, and establish a moderate deviation resul...
Random matrix serves as one of the key tools in understanding the eigen-structure of large dimension...
This paper serves to prove the thesis that a computational trick can open entirely new approaches to...
Random matrix theory is now a big subject with applications in many discip-lines of science, enginee...
This is a book for absolute beginners. If you have heard about random matrix theory, commonly denote...
Random matrix theory has many roots and many branches in mathematics, statistics, physics, computer ...
We review the development of random-matrix theory (RMT) during the last decade. We emphasize both th...
During the last twenty years, Random matrix theory (RMT) has produced numerous results that allow a ...
While many university students get introduced to the concept of statistics early in their education,...
Random matrix theory (RMT) is based on two assumptions: (1) matrix-element independence, and (2) bas...
Akemann G, Baik J, Di Francesco P, eds. The Oxford Handbook of Random Matrix Theory. Oxford: Oxford ...
This paper is a brief review of recent developments in random matrix theory. Two aspects ar...
This thesis is concerned about statistical inference for high dimensional data based on large dimens...
In recent years there has been a growing interest in connections between the statistical properties...
This book presents a unified theory of random matrices for applications in machine learning, offerin...
We review some recent developments in random matrix theory, and establish a moderate deviation resul...
Random matrix serves as one of the key tools in understanding the eigen-structure of large dimension...
This paper serves to prove the thesis that a computational trick can open entirely new approaches to...
Random matrix theory is now a big subject with applications in many discip-lines of science, enginee...
This is a book for absolute beginners. If you have heard about random matrix theory, commonly denote...
Random matrix theory has many roots and many branches in mathematics, statistics, physics, computer ...
We review the development of random-matrix theory (RMT) during the last decade. We emphasize both th...
During the last twenty years, Random matrix theory (RMT) has produced numerous results that allow a ...
While many university students get introduced to the concept of statistics early in their education,...
Random matrix theory (RMT) is based on two assumptions: (1) matrix-element independence, and (2) bas...
Akemann G, Baik J, Di Francesco P, eds. The Oxford Handbook of Random Matrix Theory. Oxford: Oxford ...
This paper is a brief review of recent developments in random matrix theory. Two aspects ar...
This thesis is concerned about statistical inference for high dimensional data based on large dimens...
In recent years there has been a growing interest in connections between the statistical properties...
This book presents a unified theory of random matrices for applications in machine learning, offerin...
We review some recent developments in random matrix theory, and establish a moderate deviation resul...
Random matrix serves as one of the key tools in understanding the eigen-structure of large dimension...
This paper serves to prove the thesis that a computational trick can open entirely new approaches to...