Distributed Optimization And Statistical Learning Via The Alternating Direction Method Of Multipliers
DOWNLOAD
READ ONLINE
Download Distributed Optimization And Statistical Learning Via The Alternating Direction Method Of Multipliers PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Distributed Optimization And Statistical Learning Via The Alternating Direction Method Of Multipliers book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Distributed Optimization And Statistical Learning Via The Alternating Direction Method Of Multipliers
DOWNLOAD
READ ONLINE
Author : Stephen Boyd
language : en
Publisher: Now Publishers Inc
Release Date : 2011
Distributed Optimization And Statistical Learning Via The Alternating Direction Method Of Multipliers written by Stephen Boyd and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
Alternating Direction Method Of Multipliers For Machine Learning
DOWNLOAD
READ ONLINE
Author : Zhouchen Lin
language : en
Publisher:
Release Date : 2022
Alternating Direction Method Of Multipliers For Machine Learning written by Zhouchen Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type of optimization problem, and the alternating direction method of multipliers (ADMM) is a commonly used algorithm to solve constrained problems, especially linearly constrained ones. Written by experts in machine learning and optimization, this is the first book providing a state-of-the-art review on ADMM under various scenarios, including deterministic and convex optimization, nonconvex optimization, stochastic optimization, and distributed optimization. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference book for users who are seeking a relatively universal algorithm for constrained problems. Graduate students or researchers can read it to grasp the frontiers of ADMM in machine learning in a short period of time.
Alternating Direction Method Of Multipliers For Machine Learning
DOWNLOAD
READ ONLINE
Author : Zhouchen Lin
language : en
Publisher: Springer Nature
Release Date : 2022-06-15
Alternating Direction Method Of Multipliers For Machine Learning written by Zhouchen Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-15 with Computers categories.
Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type of optimization problem, and the alternating direction method of multipliers (ADMM) is a commonly used algorithm to solve constrained problems, especially linearly constrained ones. Written by experts in machine learning and optimization, this is the first book providing a state-of-the-art review on ADMM under various scenarios, including deterministic and convex optimization, nonconvex optimization, stochastic optimization, and distributed optimization. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference book for users who are seeking a relatively universal algorithm for constrained problems. Graduate students or researchers can read it to grasp the frontiers of ADMM in machine learning in a short period of time.
Accelerated Optimization For Machine Learning
DOWNLOAD
READ ONLINE
Author : Zhouchen Lin
language : en
Publisher: Springer Nature
Release Date : 2020-05-29
Accelerated Optimization For Machine Learning written by Zhouchen Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-29 with Computers categories.
This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
Machine Learning And Wireless Communications
DOWNLOAD
READ ONLINE
Author : Yonina C. Eldar
language : en
Publisher: Cambridge University Press
Release Date : 2022-06-30
Machine Learning And Wireless Communications written by Yonina C. Eldar and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Technology & Engineering categories.
How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.
Artificial Neural Networks And Machine Learning Icann 2018
DOWNLOAD
READ ONLINE
Author : Věra Kůrková
language : en
Publisher: Springer
Release Date : 2018-09-26
Artificial Neural Networks And Machine Learning Icann 2018 written by Věra Kůrková and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-26 with Computers categories.
This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning.
Machine Learning Optimization And Big Data
DOWNLOAD
READ ONLINE
Author : Panos Pardalos
language : en
Publisher: Springer
Release Date : 2016-01-05
Machine Learning Optimization And Big Data written by Panos Pardalos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-05 with Computers categories.
This book constitutes revised selected papers from the First International Workshop on Machine Learning, Optimization, and Big Data, MOD 2015, held in Taormina, Sicily, Italy, in July 2015. The 32 papers presented in this volume were carefully reviewed and selected from 73 submissions. They deal with the algorithms, methods and theories relevant in data science, optimization and machine learning.
Cloud Computing Smart Grid And Innovative Frontiers In Telecommunications
DOWNLOAD
READ ONLINE
Author : Xuyun Zhang
language : en
Publisher: Springer Nature
Release Date : 2020-05-22
Cloud Computing Smart Grid And Innovative Frontiers In Telecommunications written by Xuyun Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-22 with Computers categories.
This book constitutes the refereed proceedings of the 9thInternational Conference on Cloud Computing, CloudComp 2019, and the 4th International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019, both held in Beijing, China, in December 2019. The55 full papers of both conferences were selected from 113 submissions. CloudComp 2019 presents recent advances and experiences in clouds, cloud computing and related ecosystems and business support. The papers are grouped thematically in tracks on cloud architecture and scheduling; cloud-based data analytics; cloud applications; and cloud security and privacy. SmartGIFT 2019 focus on all aspects of smart grids and telecommunications, broadly understood as the renewable generation and distributed energy resources integration, computational intelligence applications, information and communication technologies.
Machine Learning And Security
DOWNLOAD
READ ONLINE
Author : Clarence Chio
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-01-26
Machine Learning And Security written by Clarence Chio and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-26 with Computers categories.
Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself! With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
First Order And Stochastic Optimization Methods For Machine Learning
DOWNLOAD
READ ONLINE
Author : Guanghui Lan
language : en
Publisher: Springer Nature
Release Date : 2020-05-15
First Order And Stochastic Optimization Methods For Machine Learning written by Guanghui Lan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-15 with Mathematics categories.
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.