Convexity And Connectivity Of The Solution Space In Machine Learning Problems
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Convexity And Connectivity Of The Solution Space In Machine Learning Problems
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Author : Maxime Hardy
language : en
Publisher: Scientia Rerum (academic publishers), Paris
Release Date : 2019-01-24
Convexity And Connectivity Of The Solution Space In Machine Learning Problems written by Maxime Hardy and has been published by Scientia Rerum (academic publishers), Paris this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-24 with Mathematics categories.
ScientiaRerum Thesis — 2018. This thesis investigates properties of the solution space of the machine-learning problem of random pattern classification. Such properties as convexity of the space of solutions, its connectivity and clusterization are studied. Evidence has been provided recently that there exists a universality class for random pattern classification models, making it possible to study the properties of the whole set of constraint satisfaction problems using the most simple model, the perceptron with spherical constraint: it is exactly solvable and exhibits the full stack of charactetistic properties of that class. In order to obtain statistically representative treatment of the model (as opposed to the best/worst-case scenarios), we used the well established methods of theoretical physics of disordered systems (a.k.a. spin glasses). In terms of that science, this model can be interpreted as a random packing problem and demonstrates the phenomenology of slow glassy relaxation and a jamming transition. The specific property of that model is that the corresponding constraint satisfaction problems ceases to be convex. The non-convex domain is exproled in detail in this thesis and its structure is presented on a phase diagram.Publisher : Scientia Rerum (academic publishers), Paris
Decision Making Models
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Author : Tofigh Allahviranloo
language : en
Publisher: Elsevier
Release Date : 2024-07-24
Decision Making Models written by Tofigh Allahviranloo and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.
Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems, optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision making mechanisms realized under uncertainty. - Introduces mathematics of intelligent systems which provides the usage of mathematical rigor such as precise definitions, theorems, results, and proofs - Provides extended and new comprehensive methods which can be used efficiently in a fuzzy environment as well as optimization problems and related fields - Covers applications and elaborates on the usage of the developed methodology in various fields of industry such as software technologies, biomedicine, image processing, and communications
Musical Networks
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Author : Niall Griffith
language : en
Publisher: MIT Press
Release Date : 1999
Musical Networks written by Niall Griffith and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Music categories.
This volume presents the most up-to-date collection of neural network models of music and creativity gathered together in one place. Chapters by leaders in the field cover new connectionist models of pitch perception, tonality, musical streaming, sequential and hierarchical melodic structure, composition, harmonization, rhythmic analysis, sound generation, and creative evolution. The collection combines journal papers on connectionist modeling, cognitive science, and music perception with new papers solicited for this volume. It also contains an extensive bibliography of related work. Contributors Shumeet Baluja, M.I. Bellgard, Michael A. Casey, Garrison W. Cottrell, Peter Desain, Robert O. Gjerdingen, Mike Greenhough, Niall Griffith, Stephen Grossberg, Henkjan Honing, Todd Jochem, Bruce F. Katz, John F. Kolen, Edward W. Large, Michael C. Mozer, Michael P.A. Page, Caroline Palmer, Jordan B. Pollack, Dean Pomerleau, Stephen W. Smoliar, Ian Taylor, Peter M. Todd, C.P. Tsang, Gregory M. Werner
Performance Controllable Industrial Wireless Networks
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Author : Haibin Yu
language : en
Publisher: Springer Nature
Release Date : 2023-04-06
Performance Controllable Industrial Wireless Networks written by Haibin Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-06 with Technology & Engineering categories.
With the rapid proliferation of information and communications technology, industrial automation has undergone a sweeping transformation toward intelligent manufacturing. Wireless communication is widely considered to be one of the key technologies enabling intelligent manufacturing. On one hand, deterministic communication with high reliability and low latency is typically required in industrial automation applications. On the other hand, wireless communication in industrial settings is hindered by strictly limited communication resources and many other factors which mainly derive from the shared and error-prone nature of the wireless channels used. The limited communication resources and harsh channel conditions pose considerable challenges for reliable, real-time data transmission in industrial wireless networks. Resource optimization methods are vital to ensuring the deterministic performance of industrial wireless networks. Traditional resource optimization methods adopt the isolated resource optimization methods for each protocol layer, which is inherently local-optimal and leads performance uncontrollable. To focus on “Performance Controllable Industrial Wireless Networks”, this book presents thejoint resource optimization methods across multiple protocol layers for industrial wireless networks; reviews recent, major advances; and discusses the practical implementations of the proposed methods. The joint resource optimization methods discussed here will greatly benefit scientists and researchers in the areas of industrial automation and Industrial Internet of Things. To gain the most from this book, readers should have a fundamental grasp of wireless communication, scheduling theory, and convex optimization.
Fundamentals Of Orthopedic Design With Non Parametric Optimization
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Author : Musaddiq Al Ali
language : en
Publisher: Springer Nature
Release Date : 2024-03-26
Fundamentals Of Orthopedic Design With Non Parametric Optimization written by Musaddiq Al Ali and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-26 with Technology & Engineering categories.
This book introduces a fundamental understanding of orthopedic design for both engineers and medical staff. It addresses the gap and mystery that often exists between these two fields and provides a common ground for understanding. The book covers various aspects of orthopedic design, including the anatomy and biomechanics of bones and joints, the materials used in orthopedic devices, and the testing and evaluation of orthopedic devices. It also introduces computer-aided design with additive manufacturing in a practical sense, including the principles of non-parametric optimization (topology and shape optimization) in a scientific and practical way. The author provides dedicated examples and research studies to further clarify the concepts presented in the book and includes some of their own peer-reviewed papers to support the material. Additionally, it covers the practical applications of computer-aided design and additivemanufacturing in orthopedic design, including the use of virtual prototyping, computer simulation, and 3D printing techniques. The book aims to provide a comprehensive guide to orthopedic design and the latest advancements in the field.
Deep Learning Technologies
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Author : Dr.VV.Sunil Kumar
language : en
Publisher: Leilani Katie Publication
Release Date : 2025-01-22
Deep Learning Technologies written by Dr.VV.Sunil Kumar and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.
Dr.VV.Sunil Kumar, Professor, Department of Computer Science and Engineering, PBR Visvodaya Institute of Technology and Science, Kavali, SPSR Nellore, Andhra Pradesh, India. Dr.G.Vijay Kumar, Professor, Department of Computer Science and Engineering, PBR Visvodaya Institute of Technology and Science, Kavali, SPSR Nellore, Andhra Pradesh, India.
Order Analysis Deep Learning And Connections To Optimization
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Author : Johannes Jahn
language : en
Publisher: Springer Nature
Release Date : 2024-10-22
Order Analysis Deep Learning And Connections To Optimization written by Johannes Jahn and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Business & Economics categories.
This book introduces readers to order analysis and various aspects of deep learning, and describes important connections to optimization, such as nonlinear optimization as well as vector and set optimization. Besides a review of the essentials, this book consists of two main parts. The first main part focuses on the introduction of order analysis as an application-driven theory, which allows to treat order structures with an analytical approach. Applications of order analysis to nonlinear optimization, as well as vector and set optimization with fixed and variable order structures, are discussed in detail. This means there are close ties to finance, operations research, and multicriteria decision making. Deep learning is the subject of the second main part of this book. In addition to the usual basics, the focus is on gradient methods, which are investigated in the context of complex models with a large number of parameters. And a new fast variant of a gradient method is presented in this part. Finally, the deep learning approach is extended to data sets given by set-valued data. Although this set-valued approach is more computationally intensive, it has the advantage of producing more robust predictions. This book is primarily intended for researchers in the fields of optimization, order theory, or artificial intelligence (AI), but it will also benefit graduate students with a general interest in these fields. The book assumes that readers have a basic understanding of functional analysis or at least basic analysis. By unifying and streamlining existing approaches, this work will also appeal to professionals seeking a comprehensive and straightforward perspective on AI or order theory approaches.
Machine Learning Algorithms For Signal And Image Processing
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Author : Deepika Ghai
language : en
Publisher: John Wiley & Sons
Release Date : 2022-12-08
Machine Learning Algorithms For Signal And Image Processing written by Deepika Ghai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-08 with Technology & Engineering categories.
Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.
Artificial Neural Networks And Machine Learning Icann 2024
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Author : Michael Wand
language : en
Publisher: Springer Nature
Release Date : 2024-09-16
Artificial Neural Networks And Machine Learning Icann 2024 written by Michael Wand and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-16 with Computers categories.
The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17–20, 2024. The 294 full papers and 16 short papers included in these proceedings were carefully reviewed and selected from 764 submissions. The papers cover the following topics: Part I - theory of neural networks and machine learning; novel methods in machine learning; novel neural architectures; neural architecture search; self-organization; neural processes; novel architectures for computer vision; and fairness in machine learning. Part II - computer vision: classification; computer vision: object detection; computer vision: security and adversarial attacks; computer vision: image enhancement; and computer vision: 3D methods. Part III - computer vision: anomaly detection; computer vision: segmentation; computer vision: pose estimation and tracking; computer vision: video processing; computer vision: generative methods; and topics in computer vision. Part IV - brain-inspired computing; cognitive and computational neuroscience; explainable artificial intelligence; robotics; and reinforcement learning. Part V - graph neural networks; and large language models. Part VI - multimodality; federated learning; and time series processing. Part VII - speech processing; natural language processing; and language modeling. Part VIII - biosignal processing in medicine and physiology; and medical image processing. Part IX - human-computer interfaces; recommender systems; environment and climate; city planning; machine learning in engineering and industry; applications in finance; artificial intelligence in education; social network analysis; artificial intelligence and music; and software security. Part X - workshop: AI in drug discovery; workshop: reservoir computing; special session: accuracy, stability, and robustness in deep neural networks; special session: neurorobotics; and special session: spiking neural networks.
Computer Vision Eccv 2020
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Author : Andrea Vedaldi
language : en
Publisher: Springer Nature
Release Date : 2020-11-03
Computer Vision Eccv 2020 written by Andrea Vedaldi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-03 with Computers categories.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.