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Author : Chooi Mey Kwan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (959 download)
Download or read book Improving Generalization Capability of Neural Networks Through Complexity Regularization written by Chooi Mey Kwan and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Danaipong Chetchotsak
Publisher :
ISBN 13 :
Total Pages : 410 pages
Book Rating : 4.:/5 (528 download)
Download or read book Improving Generalization Capability of Neural Networks Under Conditions of Sparse Data written by Danaipong Chetchotsak and published by . This book was released on 2003 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Carlos A. Coello Coello
Publisher : Springer Science & Business Media
ISBN 13 : 3540249834
Total Pages : 927 pages
Book Rating : 4.5/5 (42 download)
Download or read book Evolutionary Multi-Criterion Optimization written by Carlos A. Coello Coello and published by Springer Science & Business Media. This book was released on 2005-02-17 with total page 927 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005. The 59 revised full papers presented together with 2 invited papers and the summary of a tutorial were carefully reviewed and selected from the 115 papers submitted. The papers are organized in topical sections on algorithm improvements, incorporation of preferences, performance analysis and comparison, uncertainty and noise, alternative methods, and applications in a broad variety of fields.
Author : Francesco Carlo Morabito
Publisher : IOS Press
ISBN 13 : 9789051993554
Total Pages : 566 pages
Book Rating : 4.9/5 (935 download)
Download or read book Advances in Intelligent Systems written by Francesco Carlo Morabito and published by IOS Press. This book was released on 1997 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Systems can be defined as systems whose design, mainly based on computational techniques, is supported, in some parts, by operations and processing skills inspired by human reasoning and behaviour. Intelligent Systems must typically operate in a scenario in which non-linearities are the rule and not as a disturbing effect to be corrected. Finally, Intelligent Systems also have to incorporate advanced sensory technology in order to simplify man-machine interactions. Several algorithms are currently the ordinary tools of Intelligent Systems. This book contains a selection of contributions regarding Intelligent Systems by experts in diverse fields. Topics discussed in the book are: Applications of Intelligent Systems in Modelling and Prediction of Environmental Changes, Cellular Neural Networks for NonLinear Filtering, NNs for Signal Processing, Image Processing, Transportation Intelligent Systems, Intelligent Techniques in Power Electronics, Applications in Medicine and Surgery, Hardware Implementation and Learning of NNs.
Author : Huchuan Lu
Publisher : Springer
ISBN 13 : 3030228088
Total Pages : 630 pages
Book Rating : 4.0/5 (32 download)
Download or read book Advances in Neural Networks – ISNN 2019 written by Huchuan Lu and published by Springer. This book was released on 2019-06-26 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.
Author : Holger Boche
Publisher : Birkhäuser
ISBN 13 : 3319730746
Total Pages : 305 pages
Book Rating : 4.3/5 (197 download)
Download or read book Compressed Sensing and Its Applications written by Holger Boche and published by Birkhäuser. This book was released on 2019-08-13 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.
Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 575 pages
Book Rating : 4./5 ( download)
Download or read book Better Deep Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-12-13 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning neural networks have become easy to define and fit, but are still hard to configure. Discover exactly how to improve the performance of deep learning neural network models on your predictive modeling projects. With clear explanations, standard Python libraries, and step-by-step tutorial lessons, you’ll discover how to better train your models, reduce overfitting, and make more accurate predictions.
Author :
Publisher :
ISBN 13 :
Total Pages : 99 pages
Book Rating : 4.:/5 (946 download)
Download or read book Radial Complexity Estimation for Improved Generalization in Artificial Neural Networks written by and published by . This book was released on 1998 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: When training an artificial neural network (ANN) for classification using backpropagation of error, the weights are usually updated by minimizing the sum-squared error on the training set. As training ensues, overtraining may be observed as the network begins to memorize the training data. This occurs because, as the magnitude of the weight vector, W, grows, the decision boundaries become overly complex in much the same way as a too-high order polynomial approximation can overfit a data set in a regression problem. Since w grows during standard backpropagation, it is important to initialize the weights with consideration to the importance of the weight vector magnitude, w. With this in mind, the expected value of the magnitude of the initial weight vector is here derived for the separate cases of each weight drawn from a normal or uniform distribution. The usefulness of this derivation is universal since the magnitude of the weight vector plays such an important role in the formation of the classification boundaries. When the network overtrains on the training data, it will not exhibit consistently low error on subsequent test data. One way to overcome this overtraining problem is to stop the training early, which limits the magnitude of the weight vector below what it would be if the training were allowed to continue until a near-global training error minimum were found. The question then is when to stop the training. Here, the relationship between training data set size and the magnitude of the weight vector providing good generalization results is empirically established using cross-validational analysis on small subsets of the training data. These results are then used to estimate at what weight vector magnitude the training should be stopped when using the full data set.
Author : China Society of Automotive Engineers
Publisher : Springer Nature
ISBN 13 : 9811620903
Total Pages : 1670 pages
Book Rating : 4.8/5 (116 download)
Download or read book Proceedings of China SAE Congress 2020: Selected Papers written by China Society of Automotive Engineers and published by Springer Nature. This book was released on 2022-01-13 with total page 1670 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings gather outstanding papers presented at the China SAE Congress 2020, held on Oct. 27-29, Shanghai, China. Featuring contributions mainly from China, the biggest carmaker as well as most dynamic car market in the world, the book covers a wide range of automotive-related topics and the latest technical advances in the industry. Many of the approaches in the book will help technicians to solve practical problems that affect their daily work. In addition, the book offers valuable technical support to engineers, researchers and postgraduate students in the field of automotive engineering.
Author : Giancarlo Fortino
Publisher : Springer Nature
ISBN 13 : 9819708923
Total Pages : 786 pages
Book Rating : 4.8/5 (197 download)
Download or read book Proceedings of Third International Conference on Computing and Communication Networks written by Giancarlo Fortino and published by Springer Nature. This book was released on with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Zhenghua Chen
Publisher : World Scientific
ISBN 13 : 9811218854
Total Pages : 327 pages
Book Rating : 4.8/5 (112 download)
Download or read book Generalization With Deep Learning: For Improvement On Sensing Capability written by Zhenghua Chen and published by World Scientific. This book was released on 2021-04-07 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data.
Author : Nuno Moniz
Publisher : Springer Nature
ISBN 13 : 3031490118
Total Pages : 606 pages
Book Rating : 4.0/5 (314 download)
Download or read book Progress in Artificial Intelligence written by Nuno Moniz and published by Springer Nature. This book was released on 2024-01-15 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 14115 and 14116 constitutes the refereed proceedings of the 22nd EPIA Conference on Progress in Artificial Intelligence, EPIA 2023, held in Faial Island, Azores, in September 2023. The 85 full papers presented in these proceedings were carefully reviewed and selected from 163 submissions. The papers have been organized in the following topical sections: ambient intelligence and affective environments; ethics and responsibility in artificial intelligence; general artificial intelligence; intelligent robotics; knowledge discovery and business intelligence; multi-agent Systems: theory and applications; natural language processing, text mining and applications; planning, scheduling and decision-making in AI; social simulation and modelling; artifical intelligence, generation and creativity; artificial intelligence and law; artificial intelligence in power and energy systems; artificial intelligence in medicine; artificial intelligence and IoT in agriculture; artificial intelligence in transportation systems; artificial intelligence in smart computing; artificial intelligence for industry and societies.
Author : Yaochu Jin
Publisher : Springer Science & Business Media
ISBN 13 : 3540330194
Total Pages : 657 pages
Book Rating : 4.5/5 (43 download)
Download or read book Multi-Objective Machine Learning written by Yaochu Jin and published by Springer Science & Business Media. This book was released on 2007-06-10 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
Author : J. P. Marques de Sá
Publisher : Springer Science & Business Media
ISBN 13 : 9783540422976
Total Pages : 344 pages
Book Rating : 4.4/5 (229 download)
Download or read book Pattern Recognition written by J. P. Marques de Sá and published by Springer Science & Business Media. This book was released on 2001 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains: Datasets -- Software tools.
Author : John Andrew Bullinaria
Publisher : World Scientific
ISBN 13 : 981238037X
Total Pages : 316 pages
Book Rating : 4.8/5 (123 download)
Download or read book Connectionist Models of Cognition and Perception written by John Andrew Bullinaria and published by World Scientific. This book was released on 2002 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist Models of Cognition and Perception collects together refereed versions of twenty-three papers presented at the Seventh Neural Computation and Psychology Workshop (NCPW7). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on connectionist modelling in psychology.The articles have the main theme of connectionist modelling of cognition and perception, and are organised into six sections, on: cell assemblies, representation, memory, perception, vision and language. This book is an invaluable resource for researchers interested in neural models of psychological phenomena.
Author : Zhidong Bai
Publisher : Springer Science & Business Media
ISBN 13 : 1441906614
Total Pages : 560 pages
Book Rating : 4.4/5 (419 download)
Download or read book Spectral Analysis of Large Dimensional Random Matrices written by Zhidong Bai and published by Springer Science & Business Media. This book was released on 2009-12-10 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random matrices. The core of the book focuses on results established under moment conditions on random variables using probabilistic methods, and is thus easily applicable to statistics and other areas of science. The book introduces fundamental results, most of them investigated by the authors, such as the semicircular law of Wigner matrices, the Marcenko-Pastur law, the limiting spectral distribution of the multivariate F matrix, limits of extreme eigenvalues, spectrum separation theorems, convergence rates of empirical distributions, central limit theorems of linear spectral statistics, and the partial solution of the famous circular law. While deriving the main results, the book simultaneously emphasizes the ideas and methodologies of the fundamental mathematical tools, among them being: truncation techniques, matrix identities, moment convergence theorems, and the Stieltjes transform. Its treatment is especially fitting to the needs of mathematics and statistics graduate students and beginning researchers, having a basic knowledge of matrix theory and an understanding of probability theory at the graduate level, who desire to learn the concepts and tools in solving problems in this area. It can also serve as a detailed handbook on results of large dimensional random matrices for practical users. This second edition includes two additional chapters, one on the authors' results on the limiting behavior of eigenvectors of sample covariance matrices, another on applications to wireless communications and finance. While attempting to bring this edition up-to-date on recent work, it also provides summaries of other areas which are typically considered part of the general field of random matrix theory.
Author : Frank-Peter Schilling
Publisher : Springer Nature
ISBN 13 : 3030583090
Total Pages : 313 pages
Book Rating : 4.0/5 (35 download)
Download or read book Artificial Neural Networks in Pattern Recognition written by Frank-Peter Schilling and published by Springer Nature. This book was released on 2020-09-01 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
