Springer Statistical Analysis for High-Dimensional Data Book

Explore the latest developments in statistical and machine learning methodologies with Statistical Analysis for High-Dimensional Data. This volume contains research contributions from The Abel Symposium held in Nyvagar, Lofoten, Norway, in May 2014. This collection focuses on the specific challenges of inference in big data environments. It is particularly useful for those working with genomic applications and complex datasets. The contributors are prominent researchers in the theory of statistics for high dimensional inference, providing a deep look into new theories and methods. Readers will find a mix of theoretical advancements and practical computational solutions. The book addresses challenging applications that arise when dealing with high-dimensional data, making it a valuable resource for academics and professionals in the fields of statistics, machine learning, and data science.