Distributed Iterative Decoding And Estimation Via Expectation Propagation
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Distributed Iterative Decoding And Estimation Via Expectation Propagation
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Author : John MacLaren Walsh
language : en
Publisher:
Release Date : 2006
Distributed Iterative Decoding And Estimation Via Expectation Propagation written by John MacLaren Walsh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Machine Learning And Wireless Communications
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Author : Yonina C. Eldar
language : en
Publisher: Cambridge University Press
Release Date : 2022-08-04
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 2022-08-04 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.
Bayesian Filtering And Smoothing
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Author : Simo Särkkä
language : en
Publisher: Cambridge University Press
Release Date : 2013-09-05
Bayesian Filtering And Smoothing written by Simo Särkkä 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 2013-09-05 with Computers categories.
A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Machine Learning And Knowledge Discovery In Databases Research Track
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Author : Danai Koutra
language : en
Publisher: Springer Nature
Release Date : 2023-09-17
Machine Learning And Knowledge Discovery In Databases Research Track written by Danai Koutra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-17 with Computers categories.
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
Sparse Regression Codes
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Author : Ramji Venkataramanan
language : en
Publisher:
Release Date : 2019-06-20
Sparse Regression Codes written by Ramji Venkataramanan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-20 with categories.
Researchers and students in modern communication and network systems will find this book an essential resource in understanding this new family of codes that will have a significant impact on such systems in the years to come.
Chips Challenging Champions
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Author : J. Schaeffer
language : en
Publisher: Elsevier
Release Date : 2002-04-17
Chips Challenging Champions written by J. Schaeffer and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-17 with Computers categories.
One of the earliest dreams of the fledgling field of artificial intelligence (AI) was to build computer programs that could play games as well as or better than the best human players. Despite early optimism in the field, the challenge proved to be surprisingly difficult. However, the 1990s saw amazing progress. Computers are now better than humans in checkers, Othello and Scrabble; are at least as good as the best humans in backgammon and chess; and are rapidly improving at hex, go, poker, and shogi. This book documents the progress made in computers playing games and puzzles. The book is the definitive source for material of high-performance game-playing programs.
Information Theory Inference And Learning Algorithms
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Author : David J. C. MacKay
language : en
Publisher: Cambridge University Press
Release Date : 2003-09-25
Information Theory Inference And Learning Algorithms written by David J. C. MacKay 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 2003-09-25 with Computers categories.
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Federated Learning
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Author : Qiang Yang
language : en
Publisher: Springer Nature
Release Date : 2020-11-25
Federated Learning written by Qiang Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Learning And Intelligent Optimization
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Author : Meinolf Sellmann
language : en
Publisher: Springer Nature
Release Date : 2023-10-24
Learning And Intelligent Optimization written by Meinolf Sellmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-24 with Mathematics categories.
This book constitutes the refereed proceedings of the 17th International Conference on Learning and Intelligent Optimization, LION-17, held in Nice, France, during June 4–8, 2023. The 40 full papers presented have been carefully reviewed and selected from 83 submissions. They focus on all aspects of unleashing the potential of integrating machine learning and optimization approaches, including automatic heuristic selection, intelligent restart strategies, predict-then-optimize, Bayesian optimization, and learning to optimize.
Advances In Neural Information Processing Systems 16
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Author : Sebastian Thrun
language : en
Publisher: MIT Press
Release Date : 2004
Advances In Neural Information Processing Systems 16 written by Sebastian Thrun and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.