Spedizione gratuita per ordini superiori a 69,99 euro.

Controllare lo stato dell'ordine

Entra a far parte di una comunità di amanti dei libri di tutto il mondo e ottieni numerosi vantaggi. Crea un account gratuito

Spedizione gratuita con Packeta per un prezzo superiore a 69.99 €

Bartolini 4.49 € Punto Poste 5.49 € Punto Poste 5.49 € Punto Bartolini 3.49 € DHL 6.99 € GLS 5.99 €

Contatto

Come acquistare

Aiuto

Il mio account

▸ Vuoto :-(

Spedizione gratuita per ordini superiori a 69,99 euro.

Mean Field Guided Machine Learning

Name: Mean Field Guided Machine Learning
Brand: Springer, Berlin
SKU: 48313106
Price: 171.49 EUR
Availability: InStock
Author: Yuhan Kang
ISBN: 9783031918582

Yuhan Kang

Hao Gao

Zhu Han

Lingua

Inglese

Libro Rigido

Codice Libristo: 48313106

Casa editrice Springer, Berlin, novembre 2024

This book explores the integration of Mean Field Game (MFG) theory with machine learning (ML), prese... Descrizione completa

Codice Libristo: 48313106

420 b

171.49 €

Magazzino esterno Inviamo tra 10-13 giorni

30 giorni per il reso

I clienti hanno acquistato anche

Cocoli - Lecture CP Éd.2020 - Cahier de compréhension élève Denis Chauvet

In brossura

9.59 €

Poslední hodiny BOX 1-3 Cassandra Clareová

In brossura

41.09 €

Bildgebende Diagnostik Akuter Intestinaler Durchblutungsstorungen Dieter Beyer

In brossura

55.29 €

Mitarbeiterbefragungen als Instrument des Change Managements Randolf Reifert

In brossura

83.09 €

Kommunikation in der Pflege Clemens Hausmann

In brossura

19.29 €

Liberte d expression justice et fraternite Charriere

In brossura

22.49 €

L'Enterrement de mozart Nyssen

Libro

32.49 €

Orhan Kemalin Romanlarinda Modernlesme; Birey ve Gündelik Hayat Mehmet Nuri Gültekin

In brossura

12.69 €

Les saisons de la Wicca Ambrosia Hawthorn

Libro

27.29 €

Engineered Minds

In brossura

13.29 €

Mitteilungen Aus Dem Hamburgischen Zoologischen Museum Und Institut. Band 50 No Contributor

Rigido

123.99 €

Jahrbuch Der Musikbibliothek Peters; Volume 11 Emil Vogel

In brossura

19.99 €

Warszawa stolica Polski wersja rosyjska Christian Parma

Rigido

8.29 €

This book explores the integration of Mean Field Game (MFG) theory with machine learning (ML), presenting both theoretical foundations and practical applications. Drawing from extensive research, it provides insights into how MFG can improve various ML techniques, including supervised learning, reinforcement learning, and federated learning.

MFG theory and ML are converging to address critical challenges in high-dimensional spaces and multi-agent systems. While ML has transformed industries by leveraging vast data and computational power, scalability and robustness remain key concerns. MFG theory, which models large populations of interacting agents, offers a mathematical framework to simplify and optimize complex systems, enhancing ML s efficiency and applicability.

By bridging these two fields, this book aims to drive innovation in scalable and robust machine learning. The integration of MFG with ML not only expands research possibilities but also paves the way for more adaptive and intelligent systems. Through this work, the authors hope to inspire further exploration and development in this promising interdisciplinary domain. With case studies and real-world examples, this book serves as a guide for researchers and students in communications and networks seeking to harness MFG s potential in advancing ML. Industry managers, practitioners and government research workers in the fields of communications and networks will find this book a valuable resource as well.