Pdf ebook: Non-negative Matrix Factorization Techniques

Pdf download ebook Non-negative Matrix Factorization Techniques

Summary: This book collects new results, concepts and further developments of NMF. The open problems discussed include, e.g. in bioinformatics: NMF and its extensio

  • Author : N.a
  • Publisher: Springer
  • ISBN: 3662483319
  • Genre: Technology & Engineering
  • Number of Pages: 194
  • Language: English
  • Views: 718
  • Downloads: 718
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Description: This book collects new results, concepts and further developments of NMF. The open problems discussed include, e.g. in bioinformatics: NMF and its extensions applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining etc. The research results previously scattered in different scientific journals and conference proceedings are methodically collected and presented in a unified form. While readers can read the book chapters sequentially, each chapter is also self-contained. This book can be a good reference work for researchers and engineers interested in NMF, and can also be used as a handbook for students and professionals seeking to gain a better understanding of the latest applications of NMF.


Pdf ebook: Machine Learning for Adaptive Many-Core Machines - A Practical Approach

Pdf download ebook Machine Learning for Adaptive Many-Core Machines - A Practical Approach

Summary: The overwhelming data produced everyday and the increasing performance and cost requirements of applications are transversal to a wide range of activities

  • Author : Noel Lopes,Bernardete Ribeiro
  • Publisher: Springer
  • ISBN: 3319069381
  • Genre: Computers
  • Number of Pages: 241
  • Language: English
  • Views: 1647
  • Downloads: 1647
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Description: The overwhelming data produced everyday and the increasing performance and cost requirements of applications are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data. This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together.


Pdf ebook: Nonnegative Matrix and Tensor Factorizations

Pdf download ebook Nonnegative Matrix and Tensor Factorizations

Summary: This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions a

  • Author : Andrzej Cichocki,Rafal Zdunek,Anh Huy Phan,Shun-ichi Amari
  • Publisher: John Wiley & Sons
  • ISBN: 9780470747285
  • Genre: Science
  • Number of Pages: 500
  • Language: English
  • Views: 1685
  • Downloads: 1685
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Description: This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features: Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors’ own recently developed techniques in the subject area. Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms. Provides a comparative analysis of the different methods in order to identify approximation error and complexity. Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.


Pdf ebook: Matrix and Tensor Factorization Techniques for Recommender Systems

Pdf download ebook Matrix and Tensor Factorization Techniques for Recommender Systems

Summary: This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights wel

  • Author : Panagiotis Symeonidis,Andreas Zioupos
  • Publisher: Springer
  • ISBN: 3319413570
  • Genre: Computers
  • Number of Pages: 102
  • Language: English
  • Views: 1060
  • Downloads: 1060
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Description: This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods.


Pdf ebook: Artificial Intelligence and Soft Computing

Pdf download ebook Artificial Intelligence and Soft Computing

Summary: The two-volume set LNAI 8467 and LNAI 8468 constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence and Soft Co

  • Author : Leszek Rutkowski,Marcin Korytkowski,Rafał Scherer,Ryszard Tadeusiewicz,Lotfi A. Zadeh,Jacek M. Zurada
  • Publisher: Springer
  • ISBN: 3319071769
  • Genre: Computers
  • Number of Pages: 822
  • Language: English
  • Views: 1465
  • Downloads: 1465
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Description: The two-volume set LNAI 8467 and LNAI 8468 constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2014, held in Zakopane, Poland in June 2014. The 139 revised full papers presented in the volumes, were carefully reviewed and selected from 331 submissions. The 69 papers included in the first volume are focused on the following topical sections: Neural Networks and Their Applications, Fuzzy Systems and Their Applications, Evolutionary Algorithms and Their Applications, Classification and Estimation, Computer Vision, Image and Speech Analysis and Special Session 3: Intelligent Methods in Databases. The 71 papers in the second volume are organized in the following subjects: Data Mining, Bioinformatics, Biometrics and Medical Applications, Agent Systems, Robotics and Control, Artificial Intelligence in Modeling and Simulation, Various Problems of Artificial Intelligence, Special Session 2: Machine Learning for Visual Information Analysis and Security, Special Session 1: Applications and Properties of Fuzzy Reasoning and Calculus and Clustering.


Pdf ebook: Computational Genomics with R

Pdf download ebook Computational Genomics with R

Summary: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated

  • Author : Altuna Akalin
  • Publisher: CRC Press
  • ISBN: 1498781861
  • Genre: Mathematics
  • Number of Pages: 440
  • Language: English
  • Views: 418
  • Downloads: 418
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Description: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.


Pdf ebook: Nonnegative Matrix Factorization

Pdf download ebook Nonnegative Matrix Factorization

Summary: Nonnegative matrix factorization (NMF) in its modern form has become a standard tool in the analysis of high-dimensional data sets. This book provides a co

  • Author : Nicolas Gillis
  • Publisher: SIAM
  • ISBN: 1611976413
  • Genre: Mathematics
  • Number of Pages: 376
  • Language: English
  • Views: 1635
  • Downloads: 1635
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Description: Nonnegative matrix factorization (NMF) in its modern form has become a standard tool in the analysis of high-dimensional data sets. This book provides a comprehensive and up-to-date account of the most important aspects of the NMF problem and is the first to detail its theoretical aspects, including geometric interpretation, nonnegative rank, complexity, and uniqueness. It explains why understanding these theoretical insights is key to using this computational tool effectively and meaningfully. Nonnegative Matrix Factorization is accessible to a wide audience and is ideal for anyone interested in the workings of NMF. It discusses some new results on the nonnegative rank and the identifiability of NMF and makes available MATLAB codes for readers to run the numerical examples presented in the book. Graduate students starting to work on NMF and researchers interested in better understanding the NMF problem and how they can use it will find this book useful. It can be used in advanced undergraduate and graduate-level courses on numerical linear algebra and on advanced topics in numerical linear algebra and requires only a basic knowledge of linear algebra and optimization.


Pdf ebook: Audio Source Separation

Pdf download ebook Audio Source Separation

Summary: This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep ne

  • Author : Shoji Makino
  • Publisher: Springer
  • ISBN: 3319730312
  • Genre: Technology & Engineering
  • Number of Pages: 385
  • Language: English
  • Views: 1911
  • Downloads: 1911
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Description: This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.


Pdf ebook: Advances in Swarm Intelligence, Part II

Pdf download ebook Advances in Swarm Intelligence, Part II

Summary: The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chon

  • Author : Ying Tan,Yuhui Shi,Yi Chai,Guoyin Wang
  • Publisher: Springer
  • ISBN: 3642215246
  • Genre: Computers
  • Number of Pages: 587
  • Language: English
  • Views: 342
  • Downloads: 342
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Description: The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.


Pdf ebook: Regularization, Optimization, Kernels, and Support Vector Machines

Pdf download ebook Regularization, Optimization, Kernels, and Support Vector Machines

Summary: Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, provi

  • Author : Johan A.K. Suykens,Marco Signoretto,Andreas Argyriou
  • Publisher: CRC Press
  • ISBN: 1482241404
  • Genre: Computers
  • Number of Pages: 525
  • Language: English
  • Views: 700
  • Downloads: 700
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Description: Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso Discusses multi-layer SVMs Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing Describes graph-based regularization methods for single- and multi-task learning Considers regularized methods for dictionary learning and portfolio selection Addresses non-negative matrix factorization Examines low-rank matrix and tensor-based models Presents advanced kernel methods for batch and online machine learning, system identification, domain adaptation, and image processing Tackles large-scale algorithms including conditional gradient methods, (non-convex) proximal techniques, and stochastic gradient descent Regularization, Optimization, Kernels, and Support Vector Machines is ideal for researchers in machine learning, pattern recognition, data mining, signal processing, statistical learning, and related areas.


Pdf ebook: Artificial Intelligence and Soft Computing – ICAISC 2006

Pdf download ebook Artificial Intelligence and Soft Computing – ICAISC 2006

Summary: This book constitutes the refereed proceedings of the 8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006, held in Zako

  • Author : Leszek Rutkowski,Ryszard Tadeusiewicz,Lotfi A. Zadeh,Jacek Zurada
  • Publisher: Springer
  • ISBN: 3540357505
  • Genre: Computers
  • Number of Pages: 1235
  • Language: English
  • Views: 686
  • Downloads: 686
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Description: This book constitutes the refereed proceedings of the 8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006, held in Zakopane, Poland, in June 2006. The 128 revised contributed papers presented are organized in topical sections on neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, rough sets, classification and clustering, image analysis and robotics, bioinformatics and medical applications, various problems of artificial intelligence.


Pdf ebook: Source Separation and Machine Learning

Pdf download ebook Source Separation and Machine Learning

Summary: Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the impor

  • Author : Jen-Tzung Chien
  • Publisher: Academic Press
  • ISBN: 0128045779
  • Genre: Technology & Engineering
  • Number of Pages: 384
  • Language: English
  • Views: 886
  • Downloads: 886
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Description: Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation. Emphasizes the modern model-based Blind Source Separation (BSS) which closely connects the latest research topics of BSS and Machine Learning Includes coverage of Bayesian learning, sparse learning, online learning, discriminative learning and deep learning Presents a number of case studies of model-based BSS (categorizing them into four modern models - ICA, NMF, NTF and DNN), using a variety of learning algorithms that provide solutions for the construction of BSS systems


Pdf ebook: Database and Expert Systems Applications

Pdf download ebook Database and Expert Systems Applications

Summary: This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems A

  • Author : Sven Hartmann,Josef Küng,Sharma Chakravarthy,Gabriele Anderst-Kotsis,A Min Tjoa,Ismail Khalil
  • Publisher: Springer
  • ISBN: 303027618X
  • Genre: Computers
  • Number of Pages: 469
  • Language: English
  • Views: 1948
  • Downloads: 1948
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Description: This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data management and analytics; data structures and data management; management and processing of knowledge; authenticity, privacy, security and trust; consistency, integrity, quality of data; decision support systems; data mining and warehousing. Part II: Distributed, parallel, P2P, grid and cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases; knowledge discovery; web services.


Pdf ebook: Partitional Clustering Algorithms

Pdf download ebook Partitional Clustering Algorithms

Summary: This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volum

  • Author : M. Emre Celebi
  • Publisher: Springer
  • ISBN: 3319092596
  • Genre: Technology & Engineering
  • Number of Pages: 415
  • Language: English
  • Views: 1130
  • Downloads: 1130
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Description: This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering, competitive learning clustering and density-based clustering. Each chapter is contributed by a leading expert in the field.


Pdf ebook: Optimization and Dynamical Systems

Pdf download ebook Optimization and Dynamical Systems

Summary: This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys tems, sign

  • Author : Uwe Helmke,John B. Moore
  • Publisher: Springer Science & Business Media
  • ISBN: 1447134672
  • Genre: Technology & Engineering
  • Number of Pages: 403
  • Language: English
  • Views: 500
  • Downloads: 500
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Description: This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys tems, signal processing, and linear algebra. The motivation for the results developed here arises from advanced engineering applications and the emer gence of highly parallel computing machines for tackling such applications. The problems solved are those of linear algebra and linear systems the ory, and include such topics as diagonalizing a symmetric matrix, singular value decomposition, balanced realizations, linear programming, sensitivity minimization, and eigenvalue assignment by feedback control. The tools are those, not only of linear algebra and systems theory, but also of differential geometry. The problems are solved via dynamical sys tems implementation, either in continuous time or discrete time , which is ideally suited to distributed parallel processing. The problems tackled are indirectly or directly concerned with dynamical systems themselves, so there is feedback in that dynamical systems are used to understand and optimize dynamical systems. One key to the new research results has been the recent discovery of rather deep existence and uniqueness results for the solution of certain matrix least squares optimization problems in geomet ric invariant theory. These problems, as well as many other optimization problems arising in linear algebra and systems theory, do not always admit solutions which can be found by algebraic methods.


Pdf ebook: Advances in Computational Environment Science

Pdf download ebook Advances in Computational Environment Science

Summary: 2012 International Conference on Environment Science and 2012 International Conference on Computer Science (ICES 2012/ICCS 2012) will be held in Australia,

  • Author : Gary Lee
  • Publisher: Springer Science & Business Media
  • ISBN: 3642279570
  • Genre: Computers
  • Number of Pages: 392
  • Language: English
  • Views: 1316
  • Downloads: 1316
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Description: 2012 International Conference on Environment Science and 2012 International Conference on Computer Science (ICES 2012/ICCS 2012) will be held in Australia, Melbourne, 15‐16 March, 2012.Volume 1 contains some new results in computational environment science. There are 47 papers were selected as the regular paper in this volume. It contains the latest developments and reflects the experience of many researchers working in different environments (universities, research centers or even industries), publishing new theories and solving new technological problems on computational environment science. The purpose of volume 1 is interconnection of diverse scientific fields, the cultivation of every possible scientific collaboration, the exchange of views and the promotion of new research targets as well as the further dissemination, the dispersion, the diffusion of the environment science, including but not limited to Ecology, Physics, Chemistry, Biology, Soil Science, Geology, Atmospheric Science and Geography We are sure that the efforts of the authors as well as the reviewers to provide high level contributions will be appreciated by the relevant scientific community. We are convinced that presented volume will be a source of knowledge and inspiration for all academic members, researchers and practitioners working in a field of the topic covered by the book.


Pdf ebook: Neural Information Processing

Pdf download ebook Neural Information Processing

Summary: The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information P

  • Author : Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu
  • Publisher: Springer
  • ISBN: 3319265555
  • Genre: Computers
  • Number of Pages: 710
  • Language: English
  • Views: 954
  • Downloads: 954
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Description: The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.


Pdf ebook: Proceedings of 2016 Chinese Intelligent Systems Conference

Pdf download ebook Proceedings of 2016 Chinese Intelligent Systems Conference

Summary: These proceedings present selected research papers from CISC’16, held in Xiamen, China. The topics include Multi-agent system, Evolutionary Computation,

  • Author : Yingmin Jia,Junping Du,Weicun Zhang,Hongbo Li
  • Publisher: Springer
  • ISBN: 9811023387
  • Genre: Computers
  • Number of Pages: 640
  • Language: English
  • Views: 631
  • Downloads: 631
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Description: These proceedings present selected research papers from CISC’16, held in Xiamen, China. The topics include Multi-agent system, Evolutionary Computation, Artificial Intelligence, Complex systems, Computation intelligence and soft computing, Intelligent control, Advanced control technology, Robotics and applications, Intelligent information processing, Iterative learning control, Machine Learning, and etc. Engineers and researchers from academia, industry, and government can get an insight view of the solutions combining ideas from multiple disciplines in the field of intelligent systems.


Pdf ebook: A Selection of Image Processing Techniques

Pdf download ebook A Selection of Image Processing Techniques

Summary: A Selection of Image Processing Techniques: From Fundamentals to Research Front focuses on seven commonly used image-processing techniques. These are de-no

  • Author : Yu-Jin Zhang
  • Publisher: CRC Press
  • ISBN: 1000487067
  • Genre: Computers
  • Number of Pages: 348
  • Language: English
  • Views: 834
  • Downloads: 834
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Description: A Selection of Image Processing Techniques: From Fundamentals to Research Front focuses on seven commonly used image-processing techniques. These are de-noising, de-blurring, repairing, de-fogging, reconstruction from projection, watermarking, and super-resolution. This book is suitable for readers who do not have a complete foundation in the principles of image technology but need to use image techniques to solve specific tasks in particular applications. Hence, elementary knowledge for further study is provided, allowing the reader to discover suitable techniques for solving practical problems and to learn the latest developments in a specific domain. This book offers readers a three-step strategy toward problem solving: first, essential principles, then, a detailed explanation, and finally, a discussion of practical and working techniques for specific tasks. Throughout, the author highlights materials pertaining to the newest developments and trends of the technologies.


Pdf ebook: User Modeling, Adaptation, and Personalization

Pdf download ebook User Modeling, Adaptation, and Personalization

Summary: This book constitutes the refereed proceedings of the 20 th International Conference on User Modeling, Adaptation, and Personalization, held in Montreal, C

  • Author : Judith Masthoff,Bamshad Mobasher,Michel Desmarais,Roger Nkambou
  • Publisher: Springer
  • ISBN: 3642314546
  • Genre: Computers
  • Number of Pages: 396
  • Language: English
  • Views: 467
  • Downloads: 467
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Description: This book constitutes the refereed proceedings of the 20 th International Conference on User Modeling, Adaptation, and Personalization, held in Montreal, Canada, in July 2012. The 22 long and 7 short papers of the Research Paper Track presented were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections on user engagement; trust; user motivation, attention, and effort; recommender systems (including topics such as matrix factorization, critiquing, noise and spam in recommender systems); user centered design and evaluation; educational data mining; modeling learners; user models in microblogging; and visualization. The Industry Paper Track covered innovative commercial implementations or applications of UMAP technologies, and experience in applying recent research advances in practice. 2 long and 1 short papers were accepted of 5 submissions.