Download or read book Efficient Online Learning Algorithms for Total Least Square Problems written by Xiangyu Kong and published by Springer Nature. This book was released on with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Total Least Squares Problem written by Sabine Van Huffel and published by SIAM. This book was released on 1991-01-01 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principles are given, the various algebraic, statistical and sensitivity properties of the problem are discussed, and generalizations are presented. Applications are surveyed to facilitate uses in an even wider range of applications. Whenever possible, comparison is made with the well-known least squares methods. A basic knowledge of numerical linear algebra, matrix computations, and some notion of elementary statistics is required of the reader; however, some background material is included to make the book reasonably self-contained.
Download or read book Principal Component Analysis Networks and Algorithms written by Xiangyu Kong and published by Springer. This book was released on 2017-01-09 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
Download or read book Proceedings of ELM 2017 written by Jiuwen Cao and published by Springer. This book was released on 2018-10-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine (ELM) 2017, held in Yantai, China, October 4–7, 2017. The book covers theories, algorithms and applications of ELM. 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 will provide 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. It gives readers a glance of the most recent advances of ELM.
Download or read book Towards Better Understanding of Algorithms and Complexity of Some Learning Problems written by Xin Yang and published by . This book was released on 2020 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present several novel results on computational problems related to supervised learning.We focus on the computational resources required by algorithms to solve learning problems. The computational resources we consider are running time, memory usage and query complexity, which is the number of positions in the input that the algorithm needs to check. Some contributions include: time-space tradeoff lower bounds for problems of learning from uniformly random labelled examples. With our methods we can obtain bounds for learning concept classes of finite functions from random evaluations even when the sample space of random inputs can be significantly smaller than the concept class of functions and the function values can be from an arbitrary finite set. A simple and efficient algorithm for approximating the John Ellipsoid of a symmetric polytope. Our algorithm is near optimal in the sense that our time complexity matches the current best verification algorithm. Experimental results suggest that our algorithm significantly outperforms existing algorithms.The first algorithm for the total least squares problem, a variant of the ordinary least squares problem, that runs in time proportional to the sparsity of the input. The core to developing our algorithm involves recent advances in randomized linear algebra. \item A generic space efficient algorithm that is based on deterministic decision trees. The first algorithm for the linear bandits problem with prior constraints.
Download or read book Systems Analytics and Integration of Big Omics Data written by Gary Hardiman and published by MDPI. This book was released on 2020-04-15 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: A “genotype" is essentially an organism's full hereditary information which is obtained from its parents. A "phenotype" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.
Download or read book Efficiency and Scalability Methods for Computational Intellect written by Igelnik, Boris and published by IGI Global. This book was released on 2013-04-30 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational modeling and simulation has developed and expanded into a diverse range of fields such as digital signal processing, image processing, robotics, systems biology, and many more; enhancing the need for a diversifying problem solving applications in this area. Efficiency and Scalability Methods for Computational Intellect presents various theories and methods for approaching the problem of modeling and simulating intellect in order to target computation efficiency and scalability of proposed methods. Researchers, instructors, and graduate students will benefit from this current research and will in turn be able to apply the knowledge in an effective manner to gain an understanding of how to improve this field.
Download or read book Reinforcement Learning written by Marco Wiering and published by Springer Science & Business Media. This book was released on 2012-03-05 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.
Download or read book Fast Algorithms for Structured Least Squares and Total Least Squares Problems written by and published by DIANE Publishing. This book was released on with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Algorithms for Least Squares Type Problems with Bounded Uncertainties written by Stanford University. Computer Science Department. Scientific Computing and Computational Mathematics Program and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Neural Networks ISNN 2007 written by Derong Liu and published by Springer Science & Business Media. This book was released on 2007-05-24 with total page 1238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation The three volume set LNCS 4491/4492/4493 constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. The 262 revised long papers and 192 revised short papers presented were carefully reviewed and selected from a total of 1.975 submissions. The papers are organized in topical sections on neural fuzzy control, neural networks for control applications, adaptive dynamic programming and reinforcement learning, neural networks for nonlinear systems modeling, robotics, stability analysis of neural networks, learning and approximation, data mining and feature extraction, chaos and synchronization, neural fuzzy systems, training and learning algorithms for neural networks, neural network structures, neural networks for pattern recognition, SOMs, ICA/PCA, biomedical applications, feedforward neural networks, recurrent neural networks, neural networks for optimization, support vector machines, fault diagnosis/detection, communications and signal processing, image/video processing, and applications of neural networks.
Download or read book ECAI 2006 written by G. Brewka and published by IOS Press. This book was released on 2006-08-10 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the summer of 1956, John McCarthy organized the famous Dartmouth Conference which is now commonly viewed as the founding event for the field of Artificial Intelligence. During the last 50 years, AI has seen a tremendous development and is now a well-established scientific discipline all over the world. Also in Europe AI is in excellent shape, as witnessed by the large number of high quality papers in this publication. In comparison with ECAI 2004, there’s a strong increase in the relative number of submissions from Distributed AI / Agents and Cognitive Modelling. Knowledge Representation & Reasoning is traditionally strong in Europe and remains the biggest area of ECAI-06. One reason the figures for Case-Based Reasoning are rather low is that much of the high quality work in this area has found its way into prestigious applications and is thus represented under the heading of PAIS.
Download or read book Nonlinear Optimization and Applications written by Gianni Pillo and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the edited texts of the lectures presented at the workshop on Nonlinear Optimization: Theory and Applications, held in Erice at the "G. Stampacchia" School of Mathematics of the "E. Majorana" International Centre for Scientific Culture June 13-21, 1995. The meeting was conceived to review and discuss recent advances and promising research trends concerning theory, algorithms, and innovative applications in the field This is a field of mathematics which is providing viable of Nonlinear Optimization. tools in engineering, in economics and in other applied sciences, and which is giving a great contribution also in the solution of the more practiced linear optimization prob lems. The meeting was attended by approximately 70 people from 18 countries. Besides the lectures, several formal and informal discussions took place. The result was a broad exposure providing a wide and deep understanding of the present research achievements in the field. We wish to express our appreciation for the active contributions of all the partici pants in the meeting. Our gratitude is due to the Ettore Majorana Center in Erice, which offered its facilities and stimulating environment: its staff was certainly instrumental for the success of the meeting. Our gratitude is also due to Francisco Facchinei and Massino Roma for the time spent in the organization of the workshop, and to Giuliana Cai for the careful typesetting of this volume.
Download or read book Urban Intelligence and Applications written by Xiaohui Yuan and published by Springer Nature. This book was released on 2020-06-25 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents selected papers from the International Conference on Urban Intelligence and Applications (ICUIA), which took place on May 10-12, 2019 in Wuhan, China. The goal of the conference was to bring together researchers, industry leaders, policy makers, and administrators to discuss emerging technologies and their applications to advance the design and implementation of intelligent utilization and management of urban assets, and thus contributing to the autonomous, reliable, and efficient operation of modern, smart cities. The papers are collated to address major themes of urban sustainability, urban infrastructure and management, smart city applications, image and signal processing, natural language processing, and machine learning for monitoring and communications applications. The book will be of interest to researchers and industrial practitioners working on geospatial theories and tools, smart city applications, urban mobility and transportation, and community well-being and management.
Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Download or read book Algorithms and Analysis for the Efficient Solution of Large Scale Linear Least Squares Problems written by Jocelyn T. Chi and published by . This book was released on 2021 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:
