Data Variant Kernel Analysis
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Author | : Yuichi Motai |
Publisher | : John Wiley & Sons |
Total Pages | : 246 |
Release | : 2015-04-27 |
Genre | : Computers |
ISBN | : 1119019346 |
Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include data formations of offline, distributed, online, cloud, and longitudinal data, used for kernel analysis to classify and predict future state. Data-Variant Kernel Analysis: Surveys the kernel analysis in the traditionally developed machine learning techniques, such as Neural Networks (NN), Support Vector Machines (SVM), and Principal Component Analysis (PCA) Develops group kernel analysis with the distributed databases to compare speed and memory usages Explores the possibility of real-time processes by synthesizing offline and online databases Applies the assembled databases to compare cloud computing environments Examines the prediction of longitudinal data with time-sequential configurations Data-Variant Kernel Analysis is a detailed reference for graduate students as well as electrical and computer engineers interested in pattern analysis and its application in colon cancer detection.
Author | : Simon McIntosh-Smith |
Publisher | : Springer Nature |
Total Pages | : 244 |
Release | : 2023-08-30 |
Genre | : Computers |
ISBN | : 303140744X |
This book constitutes the proceedings of the 19th International Workshop on OpenMP, IWOMP 2023, held in Bristol, UK, during September 13–15, 2023. The 15 full papers presented in this book were carefully reviewed and selected from 20 submissions. The papers are divided into the following topical sections: OpenMP and AI; Tasking Extensions; OpenMP Offload Experiences; Beyond Explicit GPU Support; and OpenMP Infrastructure and Evaluation.
Author | : Alexey Moskalev |
Publisher | : Springer Nature |
Total Pages | : 328 |
Release | : 2023-07-07 |
Genre | : Science |
ISBN | : 3031351762 |
This book reviews the state-of-the-art efforts to apply machine learning and AI methods for healthy aging and longevity research, diagnosis, and therapy development. The book examines the methods of machine learning and their application in the analysis of big medical data, medical images, the creation of algorithms for assessing biological age, and effectiveness of geroprotective medications. The promises and challenges of using AI to help achieve healthy longevity for the population are manifold. This volume, written by world-leading experts working at the intersection of AI and aging, provides a unique synergy of these two highly prominent fields and aims to create a balanced and comprehensive overview of the application methodology that can help achieve healthy longevity for the population. The book is accessible and valuable for specialists in AI and longevity research, as well as a wide readership, including gerontologists, geriatricians, medical specialists, and students from diverse fields, basic scientists, public and private research entities, and policy makers interested in potential intervention in degenerative aging processes using advanced computational tools.
Author | : Peyman Setoodeh |
Publisher | : John Wiley & Sons |
Total Pages | : 240 |
Release | : 2017-07-31 |
Genre | : Technology & Engineering |
ISBN | : 1118302966 |
A comprehensive treatment of cognitive radio networks and the specialized techniques used to improve wireless communications The human brain, as exemplified by cognitive radar, cognitive radio, and cognitive computing, inspires the field of Cognitive Dynamic Systems. In particular, cognitive radio is growing at an exponential rate. Fundamentals of Cognitive Radio details different aspects of the human brain and provides examples of how it can be mimicked by cognitive dynamic systems. The text offers a communication-theoretic background, including information on resource allocation in wireless networks and the concept of robustness. The authors provide a thorough mathematical background with data on game theory, variational inequalities, and projected dynamic systems. They then delve more deeply into resource allocation in cognitive radio networks. The text investigates the dynamics of cognitive radio networks from the perspectives of information theory, optimization, and control theory. It also provides a vision for the new world of wireless communications by integration of cellular and cognitive radio networks. This groundbreaking book: Shows how wireless communication systems increasingly use cognition to enhance their networks Explores how cognitive radio networks can be viewed as spectrum supply chain networks Derives analytic models for two complementary regimes for spectrum sharing (open-access and market-driven) to study both equilibrium and disequilibrium behaviors of networks Studies cognitive heterogeneous networks with emphasis on economic provisioning for resource sharing Introduces a framework that addresses the issue of spectrum sharing across licensed and unlicensed bands aimed for Pareto optimality Written for students of cognition, communication engineers, telecommunications professionals, and others, Fundamentals of Cognitive Radio offers a new generation of ideas and provides a fresh way of thinking about cognitive techniques in order to improve radio networks.
Author | : |
Publisher | : |
Total Pages | : 504 |
Release | : 1995 |
Genre | : Digital computer simulation |
ISBN | : |
Author | : Carl Edward Rasmussen |
Publisher | : MIT Press |
Total Pages | : 266 |
Release | : 2005-11-23 |
Genre | : Computers |
ISBN | : 026218253X |
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
Author | : Masashi Sugiyama |
Publisher | : Cambridge University Press |
Total Pages | : 343 |
Release | : 2012-02-20 |
Genre | : Computers |
ISBN | : 0521190177 |
This book introduces theories, methods and applications of density ratio estimation, a newly emerging paradigm in the machine learning community.
Author | : |
Publisher | : |
Total Pages | : 614 |
Release | : 2004 |
Genre | : Induction (Logic) |
ISBN | : |
Author | : Bernhard Schölkopf |
Publisher | : MIT Press |
Total Pages | : 428 |
Release | : 2004 |
Genre | : Computers |
ISBN | : 9780262195096 |
A detailed overview of current research in kernel methods and their application to computational biology.
Author | : Bernd Radig |
Publisher | : Springer Science & Business Media |
Total Pages | : 469 |
Release | : 2007-08-03 |
Genre | : Computers |
ISBN | : 3540454047 |
Sometimes milestones in the evolution of the DAGM Symposium become immediately visible. The Technical Committee decided to publish the symposium proceedings completely in English. As a consequence we successfully negotiated with Springer Verlag to publish in the international well accepted series “Lecture Notes in Computer Science”. The quality of the contributions convinced the editors and the lectors. Thanks to them and to the authors. We received 105 acceptable, good, and even excellent manuscripts. We selected carefully, using three reviewers for each anonymized paper, 58 talks and posters. Our 41 reviewers had a hard job evaluating and especially rejecting contributions. We are grateful for the time and effort they spent in this task. The program committee awarded prizes to the best papers. We are much obliged to the generous sponsors. We had three invited talks from outstanding colleagues, namely Bernhard Nebel (Robot Soccer – A Challenge for Cooperative Action and Perception), Thomas Lengauer (Computational Biology – An Interdisciplinary Challenge for Computational Pattern Recognition), and Nassir Navab (Medical and Industrial Augmented Reality: Challenges for Real Time Vision, Computer Graphics, and Mobile Computing). N. Navab even wrote a special paper for this conference, which is included in the proceedings. We were proud that we could convince well known experts to offer tutorials to our participants: H. P. Seidel, Univ. Saarbrücken – A Framework for the Acquisition, Processing, and Interactive Display of High Quality 3D Models; S. Heuel, Univ. Bonn – Projective Geometry for Grouping and Orientation Tasks; G. Rigoll, Univ.