Neural Information Processing Theory And Algorithms

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Advances In Neural Information Processing Systems 15

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Author : Suzanna Becker
language : en
Publisher: MIT Press
Release Date : 2003

Advances In Neural Information Processing Systems 15 written by Suzanna Becker and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

Proceedings of the 2002 Neural Information Processing Systems Conference.

Advances In Neural Information Processing Systems 10

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Author : Michael I. Jordan
language : en
Publisher: MIT Press
Release Date : 1998

Advances In Neural Information Processing Systems 10 written by Michael I. Jordan and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.

Advances In Neural Information Processing Systems 17

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Author : Lawrence K. Saul
language : en
Publisher: MIT Press
Release Date : 2005

Advances In Neural Information Processing Systems 17 written by Lawrence K. Saul and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.

Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (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 twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.

Advances In Neural Information Processing Systems 19

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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2007

Advances In Neural Information Processing Systems 19 written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Artificial intelligence categories.

The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.

Predicting Structured Data

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Author : Neural Information Processing Systems Foundation
language : en
Publisher: MIT Press
Release Date : 2007

Predicting Structured Data written by Neural Information Processing Systems Foundation and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Algorithms categories.

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Process Neural Networks

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Author : Xingui He
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-05

Process Neural Networks written by Xingui He and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-05 with Computers categories.

"Process Neural Network: Theory and Applications" proposes the concept and model of a process neural network for the first time, showing how it expands the mapping relationship between the input and output of traditional neural networks and enhances the expression capability for practical problems, with broad applicability to solving problems relating to processes in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are closely examined. The application methods, network construction principles, and optimization algorithms of process neural networks in practical fields, such as nonlinear time-varying system modeling, process signal pattern recognition, dynamic system identification, and process forecast, are discussed in detail. The information processing flow and the mapping relationship between inputs and outputs of process neural networks are richly illustrated. Xingui He is a member of Chinese Academy of Engineering and also a professor at the School of Electronic Engineering and Computer Science, Peking University, China, where Shaohua Xu also serves as a professor.

Beyond The Worst Case Analysis Of Algorithms

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Author : Tim Roughgarden
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-14

Beyond The Worst Case Analysis Of Algorithms written by Tim Roughgarden 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 2021-01-14 with Computers categories.

Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.

Advances In Neural Information Processing Systems 7

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Author : Gerald Tesauro
language : en
Publisher: MIT Press
Release Date : 1995

Advances In Neural Information Processing Systems 7 written by Gerald Tesauro and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.

November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems. Drawing on such disparate domains as neuroscience, cognitive science, computer science, statistics, mathematics, engineering, and theoretical physics, the papers collected in the proceedings of NIPS7 reflect the enduring scientific and practical merit of a broad-based, inclusive approach to neural information processing. The primary focus remains the study of a wide variety of learning algorithms and architectures, for both supervised and unsupervised learning. The 139 contributions are divided into eight parts: Cognitive Science, Neuroscience, Learning Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Visual Processing, and Applications. Topics of special interest include the analysis of recurrent nets, connections to HMMs and the EM procedure, and reinforcement- learning algorithms and the relation to dynamic programming. On the theoretical front, progress is reported in the theory of generalization, regularization, combining multiple models, and active learning. Neuroscientific studies range from the large-scale systems such as visual cortex to single-cell electrotonic structure, and work in cognitive scientific is closely tied to underlying neural constraints. There are also many novel applications such as tokamak plasma control, Glove-Talk, and hand tracking, and a variety of hardware implementations, with particular focus on analog VLSI.

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.”

Emotional Cognitive Neural Algorithms With Engineering Applications

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Author : Leonid Perlovsky
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-20

Emotional Cognitive Neural Algorithms With Engineering Applications written by Leonid Perlovsky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-20 with Computers categories.

Dynamic logic (DL) recently had a highest impact on the development in several areas of modeling and algorithm design. The book discusses classical algorithms used for 30 to 50 years (where improvements are often measured by signal-to-clutter ratio), and also new areas, which did not previously exist. These achievements were recognized by National and International awards. Emerging areas include cognitive, emotional, intelligent systems, data mining, modeling of the mind, higher cognitive functions, evolution of languages and other. Classical areas include detection, recognition, tracking, fusion, prediction, inverse scattering, and financial prediction. All these classical areas are extended to using mixture models, which previously was considered unsolvable in most cases. Recent neuroimaging experiments proved that the brain-mind actually uses DL. „Emotional Cognitive Neural Algorithms with Engineering Applications“ is written for professional scientists and engineers developing computer and information systems, for professors teaching modeling and algorithms, and for students working on Masters and Ph.D. degrees in these areas. The book will be of interest to psychologists and neuroscientists interested in mathematical models of the brain and min das well.