Statistical Inference via Convex Optimization

(Hardback)

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This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal st

Reviews

"For graduate students and researchers who are interested in high-dimensional statistics and its interplay with convex optimization, this book will serve as an invaluable resource."---Debashis Ghosh, International Statistical Review

Author Bio

Anatoli Juditsky is professor of applied mathematics and chair of statistics and optimization at the Multidisciplinary Institute in Artificial Intelligence at the Universit Grenoble Alpes in France. Arkadi Nemirovski is the John Hunter Chair and professor of industrial and systems engineering at the Georgia Institute of Technology. His books include Robust Optimization (Princeton).