This monograph builds on Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions by discussing tensor network models for super-compressed higher-order representation of data/parameters and cost functions, together with an outline of their applications in machine learning and data analytics. A particular emphasis is on elucidating, through graphical illustrations, that by virtue of the underlying low-rank tensor approximations and sophisticated contractions of core tensors, tensor networks have the ability to perform distributed computations on otherwise prohibitively large volume of data/parameters, thereby alleviating the curse of dimensionality. The usefulness of this concept is illustrated over a number of applied areas, including generalized regression and classification, generalized eigenvalue decomposition and in the optimization of deep neural networks. The monograph focuses on tensor train (TT) and Hierarchical Tucker (HT) decompositions and their extensions, and on demonstrating the ability of tensor networks to provide scalable solutions for a variety of otherwise intractable large-scale optimization problems. Tensor Networks for Dimensionality Reduction and Large-scale Optimization Parts 1 and 2 can be used as stand-alone texts, or together as a comprehensive review of the exciting field of low-rank tensor networks and tensor decompositions. See also: Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions. ISBN 978-1-68083-222-8

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

Description de la librairie

Hello! Ria Christie Collections is an online venture that was initially set up in 2012 to sell books. We do not have a physical high street store. We are professional online booksellers. We only sell brand new books in perfect condition that we source from various suppliers and the publishers. Primarily, our aim is to provide an excellent service to all our customers. We always work as a team to achieve this. Our other objectives are to: 1. Ensure that all our products reach their destination quickly in a safe and secure manner 2. Answer to all our customer queries within 24 hours 3. Ensure that our customers are happy with their purchases 4. Provide all the items at a competitive price 5. Always listen to our customers Ria Christie Collections is not a registered company. It is a Sole Trader venture. Other key information is shown below: Contact Person Name: Rakesh Luchmun (Mr) Storefront Name: Ria Christie Collections Place of Establishment Address: Suite B; ARUN House; ARUN Building Arundel Road Uxbridge UB8 2RR United Kingdom E-Mail Address: riachristie@hotmail.co.uk VAT Number: GB 160 5650 25 We always work hard and aim to comply with all of Abebooks Policies. If you have any issues, please do not hesitate to write to us whether before or after a purchase. We promise to reply to you promptly and, in any case, within 24 hours. Thank you kindly! Yours sincerely Mr Rakesh Luchmun (Founder) and the Ria Christie Collections Team

Visitez la page d�accueil du vendeur

Informations commerciales relatives au vendeur

Ryefield Investments Limited
175 Pield Heath Road, Uxbridge, UB8 3NL, United Kingdom

Conditions de vente :

All Returns and Refund are as per Abebooks policies.

Conditions de livraison :

Orders usually ship within 2 business days. If your book order is heavy or oversized, we may contact you to let you know extra shipping is required. Thank you!

Modes de paiement
accept�s par le vendeur

Ajouter aux demandes de livres

Articles li�s � Tensor Networks for Dimensionality Reduction and Large-Scale...

Tensor Networks for Dimensionality Reduction and Large-Scale Optimization: Part 2 Applications and Future Perspectives (Foundations and Trends(r) in Machine Learning)

Cichocki, Andrzej; Lee, Namgil; Oseledets, Ivan; Phan, Anh-Huy; Zhao, Qibin; Mandic, Danilo P

Neuf(s) - Couverture souple

Informations commerciales relatives au vendeur