Sampling Techniques For Supervised Or Unsupervised Tasks
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Sampling Techniques For Supervised Or Unsupervised Tasks
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Author : Frédéric Ros
language : en
Publisher: Springer Nature
Release Date : 2019-10-26
Sampling Techniques For Supervised Or Unsupervised Tasks written by Frédéric Ros and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-26 with Technology & Engineering categories.
This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the “curse of dimensionality”, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task. Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks; Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality; Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. "This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge." M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas "In science the difficulty is not to have ideas, but it is to make them work" From Carlo Rovelli
Data Science Concepts And Techniques With Applications
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Author : Usman Qamar
language : en
Publisher: Springer Nature
Release Date : 2023-04-02
Data Science Concepts And Techniques With Applications written by Usman Qamar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-02 with Computers categories.
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Computers categories.
This book constitutes the proceedings of the Second International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022, held in Bragança, Portugal, in October 2022. The 53 full papers and 3 short papers were thoroughly reviewed and selected from 145 submissions. They are organized in the topical sections on Machine and Deep Learning; Optimization; Artificial Intelligence; Optimization in Control Systems Design; Measurements with the Internet of Things; Trends in Engineering Education; Advances and Optimization in Cyber-Physical Systems; and Computer vision based on learning algorithms.
Multi Objective Combinatorial Optimization Problems And Solution Methods
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Author : Mehdi Toloo
language : en
Publisher: Academic Press
Release Date : 2022-02-09
Multi Objective Combinatorial Optimization Problems And Solution Methods written by Mehdi Toloo and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-09 with Science categories.
Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. - Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications - Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature - Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms
Computational Science And Its Applications Iccsa 2021
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Author : Osvaldo Gervasi
language : en
Publisher: Springer Nature
Release Date : 2021-09-11
Computational Science And Its Applications Iccsa 2021 written by Osvaldo Gervasi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-11 with Computers categories.
The ten-volume set LNCS 12949 – 12958 constitutes the proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, which was held in Cagliari, Italy, during September 13 – 16, 2021. The event was organized in a hybrid mode due to the Covid-19 pandemic.The 466 full and 18 short papers presented in these proceedings were carefully reviewed and selected from 1588 submissions. The books cover such topics as multicore architectures, computational astrochemistry, mobile and wireless security, sensor networks, open source software, collaborative and social computing systems and tools, computational geometry, applied mathematics human computer interaction, software design engineering, and others. Part V of the set includes the the proceedings on the following workshops: International Workshop on Computational Geometry and Applications (CGA 2021); International Workshop on Collaborative Intelligence in Multimodal Applications (CIMA 2021); International Workshop on Computational Science and HPC (CSHPC 2021); International Workshop on Computational Optimization and Applications (COA 2021); International Workshop on Cities, Technologies and Planning (CTP 2021); International Workshop on Computational Astrochemistry (CompAstro 2021); International Workshop on Advanced Modeling E-Mobility in Urban Spaces (DEMOS 2021).The chapters "On Local Convergence of Stochastic Global Optimization Algorithms" and "Computing Binding Energies of Interstellar Molecules by Semiempirical Quantum Methods: Comparison between DFT and GFN2 on Crystalline Ice" are published open access under a CC BY license (Creative Commons Attribution 4.0 International License).
Computer Vision Eccv 2024
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Author : Aleš Leonardis
language : en
Publisher: Springer Nature
Release Date : 2024-11-20
Computer Vision Eccv 2024 written by Aleš Leonardis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-20 with Computers categories.
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They 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; motion estimation.
Innovation And Competitiveness In Industry 4 0 Based On Intelligent Systems
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Author : Luis Carlos Méndez-González
language : en
Publisher: Springer Nature
Release Date : 2023-06-16
Innovation And Competitiveness In Industry 4 0 Based On Intelligent Systems written by Luis Carlos Méndez-González and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-16 with Technology & Engineering categories.
This book presents a series of applications of different techniques found in Industry 4.0 with relation to productivity, continuous improvement, quality, decision systems, software development, and automation systems. The techniques used throughout this book allow the reader to replicate the results obtained towards different types of companies that wish to undertake in the new era of the digital industrial revolution. This book can also help students from different areas of engineering to understand how the use of new technologies is applied to solve current relevant problems and how they give the possibility of constant innovation in the different industrial sectors. This is accomplished through the analysis of illustrative case studies, descriptive methodologies and structured insights that are provided through the different considered techniques.
International Conference On Communication Computing And Electronics Systems
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Author : V. Bindhu
language : en
Publisher: Springer Nature
Release Date : 2021-03-25
International Conference On Communication Computing And Electronics Systems written by V. Bindhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-25 with Technology & Engineering categories.
This book includes high-quality papers presented at the International Conference on Communication, Computing and Electronics Systems 2020, held at the PPG Institute of Technology, Coimbatore, India, on 21–22 October 2020. The book covers topics such as automation, VLSI, embedded systems, integrated device technology, satellite communication, optical communication, RF communication, microwave engineering, artificial intelligence, deep learning, pattern recognition, Internet of Things, precision models, bioinformatics, and healthcare informatics.
Informed Machine Learning
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Author : Daniel Schulz
language : en
Publisher: Springer Nature
Release Date : 2025-05-11
Informed Machine Learning written by Daniel Schulz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-11 with Mathematics categories.
This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care over manufacturing and material science to more advanced combinations with deep learning, say, in the form of physical informed neural networks. The book is intended for those interested in modern informed machine learning for a wide range of practical applications where the aspect of small data sets is a challenge. Machine Learning with small amounts of data? After the recent success of Artificial Intelligence based on training with massive amounts of data, this idea may sound exotic. However, it addresses crucial needs of practitioners in industry. While many industrial applications stand to benefit from the use of AI, the amounts of data needed by current learning paradigms are often hard to come by in industrial settings. As an alternative, learning methods and models are called for which integrate other sources of knowledge in order to compensate for the lack of data. This is where the principle of “Informed Machine Learning” comes into play. Informed Machine Learning combines purely data driven learning and knowledge-based techniques to learn from both data and knowledge. This has several advantages. It reduces the need for data, it often results in smaller, less complex and more robust models, and even makes machine learning applicable in settings where data is scarce. The kind of knowledge to be incorporated into learning processes can take many different forms, for example, differential equations, analytical models, simulation results, logical rules, knowledge graphs, or human feedback which makes the approach overall very powerful and widely applicable.
Translational Applications Of Neuroimaging
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Author : Stavros Skouras
language : en
Publisher: Frontiers Media SA
Release Date : 2024-04-04
Translational Applications Of Neuroimaging written by Stavros Skouras and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-04 with Science categories.
Despite substantial progress in the development of neuroimaging methodologies, translational applications of neuroimaging remain scarce. This Research Topic invites article submissions that present promising neuroimaging applications and methods addressing critical needs for improving health outcomes. These may include Original Research, Clinical Trial, Systematic Review or Methods articles that investigate neuroimaging metrics as outcome measures or in combination with neural perturbation techniques (e.g., neurofeedback, neurostimulation), other translational applications (e.g., guiding neurosurgery). To foster debate, we also welcome critical Review, Opinion, and Perspective articles that survey the field and its progress towards clinical utility.