Contact
Comment faire ses achats
Livraison
Guide d'achat
Optimization Algorithms for Distributed Machine Learning
Anglais
110 b
Jusqu'à 30 jours pour les retours
This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.
À propos du livre
Anglais
Offrez ce livre dès aujourd'hui
C’est simple
1 Ajouter au panier et choisir l'option Livrer comme cadeau à la caisse. 2 Nous vous enverrons un bon d'achat 3 Le livre arrivera à l'adresse du destinataireBonjour ! Je suis Libroamiko, votre conseiller littéraire.
Comment puis-je vous aider ?