Electronic Resource

High dimensional probability VI

---

This is a collection of papers by participants at High Dimensional Probability VI Meeting held from October 9-14, 2011 at the Banff International Research Station in Banff, Alberta, Canada.

High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other areas of mathematics, statistics, and computer science. These include random matrix theory, nonparametric statistics, empirical process theory, statistical learning theory, concentration of measure phenomena, strong and weak approximations, distribution function estimation in high dimensions, combinatorial optimization, and random graph theory.

The papers in this volume show that HDP theory continues to develop new tools, methods, techniques and perspectives to analyze the random phenomena. Both researchers and advanced students will find this book of great use for learning about new avenues of research.​

---

Ketersediaan

Informasi Detail

Judul Seri

-

No. Panggil

E667

Penerbit

New York : Springer, NY., 2013

Deskripsi Fisik

xiii, 374 hlm.

Bahasa

English

ISBN/ISSN

9783034804905

Klasifikasi

NONE

Tipe Isi

text

Tipe Media

computer

Tipe Pembawa

online resource

Edisi

Ed.1

Subjek

Aplikasi Matematika dalam Ilmu Komputer

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Christian Houdré, David M. Mason, Jan Rosiński, Jon A. Wellner

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar