Meta Learning Computational Intelligence Architectures
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Meta Learning Computational Intelligence Architectures
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Author : Ryan James Meuth
language : en
Publisher:
Release Date : 2009
Meta Learning Computational Intelligence Architectures written by Ryan James Meuth and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computational intelligence categories.
"In computational intelligence, the term 'memetic algorithm' has come to be associated with the algorithmic pairing of a global search method with a local search method. In a sociological context, a 'meme' has been loosely defined as a unit of cultural information, the social analog of genes for individuals. Both of these definitions are inadequate, as 'memetic algorithm' is too specific, and ultimately a misnomer, as much as a 'meme' is defined too generally to be of scientific use. In this dissertation the notion of memes and meta-learning is extended from a computational viewpoint and the purpose, definitions, design guidelines and architecture for effective meta-learning are explored. The background and structure of meta-learning architectures is discussed, incorporating viewpoints from psychology, sociology, computational intelligence, and engineering. The benefits and limitations of meme-based learning are demonstrated through two experimental case studies -- Meta-Learning Genetic Programming and Meta- Learning Traveling Salesman Problem Optimization. Additionally, the development and properties of several new algorithms are detailed, inspired by the previous case-studies. With applications ranging from cognitive science to machine learning, meta-learning has the potential to provide much-needed stimulation to the field of computational intelligence by providing a framework for higher order learning"--Abstract, leaf iii
Meta Learning In Computational Intelligence
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Author : Norbert Jankowski
language : en
Publisher: Springer
Release Date : 2011-06-10
Meta Learning In Computational Intelligence written by Norbert Jankowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-10 with Computers categories.
Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Meta Learning With Medical Imaging And Health Informatics Applications
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Author : Hien Van Nguyen
language : en
Publisher: Academic Press
Release Date : 2022-09-24
Meta Learning With Medical Imaging And Health Informatics Applications written by Hien Van Nguyen and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-24 with Computers categories.
Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks' fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks.This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. - First book on applying Meta Learning to medical imaging - Pioneers in the field as contributing authors to explain the theory and its development - Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly
Beyond Databases Architectures And Structures Advanced Technologies For Data Mining And Knowledge Discovery
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Author : Stanisław Kozielski
language : en
Publisher: Springer
Release Date : 2016-04-28
Beyond Databases Architectures And Structures Advanced Technologies For Data Mining And Knowledge Discovery written by Stanisław Kozielski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-28 with Computers categories.
This book constitutes the refereed proceedings of the 12th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2016, held in Ustroń, Poland, in May/June 2016. It consists of 57 carefully reviewed papers selected from 152 submissions. The papers are organized in topical sections, namely artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; data warehousing and OLAP; natural language processing, ontologies and semantic Web; bioinformatics and biomedical data analysis; data processing tools; novel applications of database systems.
Metalearning
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Author : Pavel Brazdil
language : en
Publisher: Springer Nature
Release Date : 2022-02-22
Metalearning written by Pavel Brazdil and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Computers categories.
This open access book offers a comprehensive and thorough introduction to almost all aspects of metalearning and automated machine learning (AutoML), covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience. As one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, AutoML is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user. This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence.
International Conference On Intelligent Computing Intelligent Computing
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Author : De-Shuang Huang
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-08-04
International Conference On Intelligent Computing Intelligent Computing written by De-Shuang Huang 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 2006-08-04 with Computers categories.
This book constitutes the refereed proceedings of the International Conference on Intelligent Computing, ICIC 2006, held in Kunming, China, August 2006. The book collects 161 carefully chosen and revised full papers. Topical sections include neural networks, evolutionary computing and genetic algorithms, kernel methods, combinatorial and numerical optimization, multiobjective evolutionary algorithms, neural optimization and dynamic programming, as well as case-based reasoning and probabilistic reasoning.
Biologically Inspired Cognitive Architectures 2018
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Author : Alexei V. Samsonovich
language : en
Publisher: Springer
Release Date : 2018-08-23
Biologically Inspired Cognitive Architectures 2018 written by Alexei V. Samsonovich and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-23 with Technology & Engineering categories.
The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, from classical artificial intelligence to linguistics, from neuro- and social sciences to design and creativity, among others. The chapters, based on contributions presented at the Ninth Annual Meeting of the BICA Society, held in on August 23-24, 2018, in Prague, Czech Republic, discuss emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. All in all, the book provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.
Meta Learning In Decision Tree Induction
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Author : Krzysztof Grąbczewski
language : en
Publisher: Springer
Release Date : 2013-09-11
Meta Learning In Decision Tree Induction written by Krzysztof Grąbczewski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-11 with Technology & Engineering categories.
The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimental methodology and evaluation framework is provided. Meta-learning is discussed in great detail in the second half of the book. The exposition starts by presenting a comprehensive review of many meta-learning approaches explored in the past described in literature, including for instance approaches that provide a ranking of algorithms. The approach described can be related to other work that exploits planning whose aim is to construct data mining workflows. The book stimulates interchange of ideas between different, albeit related, approaches.
Meta Learning In Computational Intelligence
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Author : Norbert Jankowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-10
Meta Learning In Computational Intelligence written by Norbert Jankowski 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 2011-06-10 with Computers categories.
Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
The Intelligent Machine An Introduction To Artificial Intelligence
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Author : Dr. Ashwani Kumar
language : en
Publisher: Chyren Publication
Release Date : 2025-07-09
The Intelligent Machine An Introduction To Artificial Intelligence written by Dr. Ashwani Kumar and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-09 with Antiques & Collectibles categories.