Extreme Learning

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Artificial Neural Networks and Machine Learning – ICANN 2018

Author : Věra Kůrková,Yannis Manolopoulos,Barbara Hammer,Lazaros Iliadis,Ilias Maglogiannis
Publisher : Springer
Page : 632 pages
File Size : 47,9 Mb
Release : 2018-09-25
Category : Computers
ISBN : 9783030014216

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Artificial Neural Networks and Machine Learning – ICANN 2018 by Věra Kůrková,Yannis Manolopoulos,Barbara Hammer,Lazaros Iliadis,Ilias Maglogiannis Pdf

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 139 full and 28 short papers as well as 41 full poster papers and 41 short poster 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.

Document Processing Using Machine Learning

Author : Sk Md Obaidullah,KC Santosh,Teresa Goncalves,Nibaran Das,Kaushik Roy
Publisher : CRC Press
Page : 148 pages
File Size : 55,6 Mb
Release : 2019-11-25
Category : Computers
ISBN : 9781000739831

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Document Processing Using Machine Learning by Sk Md Obaidullah,KC Santosh,Teresa Goncalves,Nibaran Das,Kaushik Roy Pdf

Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.

Machine Learning and Cybernetics

Author : Xizhao Wang,Witold Pedrycz,Patrick Chan,Qiang He
Publisher : Springer
Page : 462 pages
File Size : 53,6 Mb
Release : 2014-12-04
Category : Computers
ISBN : 9783662456521

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Machine Learning and Cybernetics by Xizhao Wang,Witold Pedrycz,Patrick Chan,Qiang He Pdf

This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.

Recent Trends in Information and Communication Technology

Author : Faisal Saeed,Nadhmi Gazem,Srikanta Patnaik,Ali Saleh Saed Balaid,Fathey Mohammed
Publisher : Springer
Page : 930 pages
File Size : 54,9 Mb
Release : 2017-05-24
Category : Technology & Engineering
ISBN : 9783319594279

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Recent Trends in Information and Communication Technology by Faisal Saeed,Nadhmi Gazem,Srikanta Patnaik,Ali Saleh Saed Balaid,Fathey Mohammed Pdf

This book presents 94 papers from the 2nd International Conference of Reliable Information and Communication Technology 2017 (IRICT 2017), held in Johor, Malaysia, on April 23–24, 2017. Focusing on the latest ICT innovations for data engineering, the book presents several hot research topics, including advances in big data analysis techniques and applications; mobile networks; applications and usability; reliable communication systems; advances in computer vision, artificial intelligence and soft computing; reliable health informatics and cloud computing environments, e-learning acceptance models, recent trends in knowledge management and software engineering; security issues in the cyber world; as well as society and information technology.

Learning and Intelligent Optimization

Author : Meinolf Sellmann,Kevin Tierney
Publisher : Springer Nature
Page : 628 pages
File Size : 47,7 Mb
Release : 2023-11-25
Category : Mathematics
ISBN : 9783031445057

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Learning and Intelligent Optimization by Meinolf Sellmann,Kevin Tierney Pdf

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.

5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

Author : Anandakumar Haldorai,Arulmurugan Ramu,Sudha Mohanram
Publisher : Springer Nature
Page : 221 pages
File Size : 44,5 Mb
Release : 2023-06-05
Category : Technology & Engineering
ISBN : 9783031283246

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5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing by Anandakumar Haldorai,Arulmurugan Ramu,Sudha Mohanram Pdf

This book features the proceedings of the 5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2022). The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.

Neural Information Processing

Author : Derong Liu,Shengli Xie,Yuanqing Li,Dongbin Zhao,El-Sayed M. El-Alfy
Publisher : Springer
Page : 951 pages
File Size : 47,5 Mb
Release : 2017-11-07
Category : Computers
ISBN : 9783319700878

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Neural Information Processing by Derong Liu,Shengli Xie,Yuanqing Li,Dongbin Zhao,El-Sayed M. El-Alfy Pdf

The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.

Proceedings of ELM-2015 Volume 1

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 532 pages
File Size : 42,7 Mb
Release : 2015-12-31
Category : Technology & Engineering
ISBN : 9783319283975

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Proceedings of ELM-2015 Volume 1 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

Deep Learning for Data Analytics

Author : Himansu Das,Chittaranjan Pradhan,Nilanjan Dey
Publisher : Academic Press
Page : 220 pages
File Size : 52,7 Mb
Release : 2020-05-29
Category : Science
ISBN : 9780128226087

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Deep Learning for Data Analytics by Himansu Das,Chittaranjan Pradhan,Nilanjan Dey Pdf

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy. The authors of this book focus on suitable data analytics methods to solve complex real world problems such as medical image recognition, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks, recurrent neural networks, and deep belief networks can be used to help resolve problems in applications such as natural language processing, speech recognition, computer vision, bioinoformatics, audio recognition, drug design, and medical image analysis. Presents the latest advances in Deep Learning for data analytics and biomedical engineering applications. Discusses Deep Learning techniques as they are being applied in the real world of biomedical engineering and data science, including Deep Learning networks, deep feature learning, deep learning toolboxes, performance evaluation, Deep Learning optimization, deep auto-encoders, and deep neural networks Provides readers with an introduction to Deep Learning, along with coverage of deep belief networks, convolutional neural networks, Restricted Boltzmann Machines, data analytics basics, enterprise data science, predictive analysis, optimization for Deep Learning, and feature selection using Deep Learning

Proceedings of ELM-2014 Volume 2

Author : Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh
Publisher : Springer
Page : 400 pages
File Size : 48,8 Mb
Release : 2014-12-09
Category : Technology & Engineering
ISBN : 9783319140667

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Proceedings of ELM-2014 Volume 2 by Jiuwen Cao,Kezhi Mao,Erik Cambria,Zhihong Man,Kar-Ann Toh Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.

Learning, Design, and Technology

Author : J. Michael Spector,Barbara B. Lockee,Marcus D. Childress
Publisher : Springer Nature
Page : 4144 pages
File Size : 48,8 Mb
Release : 2023-11-15
Category : Education
ISBN : 9783319174617

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Learning, Design, and Technology by J. Michael Spector,Barbara B. Lockee,Marcus D. Childress Pdf

The multiple, related fields encompassed by this Major Reference Work represent a convergence of issues and topics germane to the rapidly changing segments of knowledge and practice in educational communications and technology at all levels and around the globe. There is no other comparable work that is designed not only to gather vital, current, and evolving information and understandings in these knowledge segments but also to be updated on a continuing basis in order to keep pace with the rapid changes taking place in the relevant fields. The Handbook is composed of substantive (5,000 to 15,000 words), peer-reviewed entries that examine and explicate seminal facets of learning theory, research, and practice. It provides a broad range of relevant topics, including significant developments as well as innovative uses of technology that promote learning, performance, and instruction. This work is aimed at researchers, designers, developers, instructors, and other professional practitioners.

Proceedings of ELM 2021

Author : Kaj-Mikael Björk
Publisher : Springer Nature
Page : 179 pages
File Size : 52,6 Mb
Release : 2023-01-18
Category : Technology & Engineering
ISBN : 9783031216787

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Proceedings of ELM 2021 by Kaj-Mikael Björk Pdf

This book contains papers from the International Conference on Extreme Learning Machine 2021, which was held in virtual on December 15–16, 2021. Extreme learning machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. This conference provides a forum for academics, researchers, and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. This book covers theories, algorithms, and applications of ELM. It gives readers a glance of the most recent advances of ELM.

Nature-Inspired Optimization Methodologies in Biomedical and Healthcare

Author : Janmenjoy Nayak,Asit Kumar Das,Bighnaraj Naik,Saroj K. Meher,Sheryl Brahnam
Publisher : Springer Nature
Page : 304 pages
File Size : 52,9 Mb
Release : 2022-11-14
Category : Technology & Engineering
ISBN : 9783031175442

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Nature-Inspired Optimization Methodologies in Biomedical and Healthcare by Janmenjoy Nayak,Asit Kumar Das,Bighnaraj Naik,Saroj K. Meher,Sheryl Brahnam Pdf

This book introduces a variety of well-proven and newly developed nature-inspired optimization algorithms solving a wide range of real-life biomedical and healthcare problems. Few solo and hybrid approaches are demonstrated in a lucid manner for the effective integration and finding solution for a large-scale complex healthcare problem. In the present bigdata-based computing scenario, nature-inspired optimization techniques present adaptive mechanisms that permit the understanding of complex data and altering environments. This book is a voluminous collection for the confront faced by the healthcare institutions and hospitals for practical analysis, storage, and data analysis. It explores the distinct nature-inspired optimization-based approaches that are able to handle more accurate outcomes for the current biomedical and healthcare problems. In addition to providing a state-of-the-art and advanced intelligent methods, it also enlightens an insight for solving diversified healthcare problems such as cancer and diabetes.

International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019)

Author : Francisco Martínez Álvarez,Alicia Troncoso Lora,José António Sáez Muñoz,Héctor Quintián,Emilio Corchado
Publisher : Springer
Page : 350 pages
File Size : 48,7 Mb
Release : 2019-04-27
Category : Technology & Engineering
ISBN : 9783030200053

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International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019) by Francisco Martínez Álvarez,Alicia Troncoso Lora,José António Sáez Muñoz,Héctor Quintián,Emilio Corchado Pdf

This volume presents papers presented at CISIS 2019 and ICEUTE 2019, held in the beautiful and historic city of Seville (Spain) in May 2019. The 12th CISIS 2019 conference offered a meeting opportunity for academic and industry-related researchers form the various communities of computational intelligence, information security and data mining, and the need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, was the catalyst and the aggregation stimulus for the event. The book covers current topics such as cryptographic and data analytics solutions to fulfil least minimum privilege and endorse least minimum effort in information systems. The book also includes 15 papers from the 10th ICEUTE 2019, covering topics like new approaches to assess competencies and innovation in computer science education.

Proceedings of ELM-2015 Volume 2

Author : Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse
Publisher : Springer
Page : 516 pages
File Size : 48,7 Mb
Release : 2016-01-02
Category : Technology & Engineering
ISBN : 9783319283739

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Proceedings of ELM-2015 Volume 2 by Jiuwen Cao,Kezhi Mao,Jonathan Wu,Amaury Lendasse Pdf

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.