Download Advances In Independent Component Analysis And Learning Machines Book PDF

Download full Advances In Independent Component Analysis And Learning Machines books PDF, EPUB, Tuebl, Textbook, Mobi or read online Advances In Independent Component Analysis And Learning Machines anytime and anywhere on any device. Get free access to the library by create an account, fast download and ads free. We cannot guarantee that every book is in the library.

Advances in Independent Component Analysis and Learning Machines

Advances in Independent Component Analysis and Learning Machines
  • Author : Ella Bingham,Samuel Kaski,Jorma Laaksonen,Jouko Lampinen
  • Publisher :Unknown
  • Release Date :2015-05-14
  • Total pages :328
  • ISBN : 9780128028070
GET BOOK HERE

Summary : In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm Unsupervised deep learning Machine vision and image retrieval A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning. A diverse set of application fields, ranging from machine vision to science policy data. Contributions from leading researchers in the field.

Recent Advances in Big Data and Deep Learning

Recent Advances in Big Data and Deep Learning
  • Author : Luca Oneto,Nicolò Navarin,Alessandro Sperduti,Davide Anguita
  • Publisher :Unknown
  • Release Date :2019-04-02
  • Total pages :392
  • ISBN : 9783030168414
GET BOOK HERE

Summary : This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.

Biometrics—Advances in Research and Application: 2013 Edition

Biometrics—Advances in Research and Application: 2013 Edition
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2013-06-21
  • Total pages :140
  • ISBN : 9781481685764
GET BOOK HERE

Summary : Biometrics—Advances in Research and Application: 2013 Edition is a ScholarlyBrief™ that delivers timely, authoritative, comprehensive, and specialized information about ZZZAdditional Research in a concise format. The editors have built Biometrics—Advances in Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about ZZZAdditional Research in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Biometrics—Advances in Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Advances in Web-Based Learning

Advances in Web-Based Learning
  • Author : Joseph Fong,Chu Ting Cheung,Hong Va Leong,Qing Li
  • Publisher :Unknown
  • Release Date :2003-08-02
  • Total pages :442
  • ISBN : 9783540456896
GET BOOK HERE

Summary : This book constitutes the refereed proceedings of the First International Conference on Web-Based Learning, ICWL 2002, held in Hong Kong, China in August 2002.The 34 revised full papers presented together with an invited keynote paper were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on system modeling and architectures, distance learning systems engineering, collaborative systems, experiences in distance learning, databases and data mining, and multimedia.

Advances in Machine Learning and Cybernetics

Advances in Machine Learning and Cybernetics
  • Author : Daniel S. Yeung,Zhi-Qiang Liu,Xi-Zhao Wang,Hong Yan
  • Publisher :Unknown
  • Release Date :2006-04-18
  • Total pages :1110
  • ISBN : 9783540335849
GET BOOK HERE

Summary : This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, held in Guangzhou, China in August 2005. The 114 revised full papers of this volume are organized in topical sections on agents and distributed artificial intelligence, control, data mining and knowledge discovery, fuzzy information processing, learning and reasoning, machine learning applications, neural networks and statistical learning methods, pattern recognition, vision and image processing.

Advances in Independent Component Analysis

Advances in Independent Component Analysis
  • Author : Mark Girolami
  • Publisher :Unknown
  • Release Date :2012-12-06
  • Total pages :284
  • ISBN : 9781447104438
GET BOOK HERE

Summary : Independent Component Analysis (ICA) is a fast developing area of intense research interest. Following on from Self-Organising Neural Networks: Independent Component Analysis and Blind Signal Separation, this book reviews the significant developments of the past year. It covers topics such as the use of hidden Markov methods, the independence assumption, and topographic ICA, and includes tutorial chapters on Bayesian and variational approaches. It also provides the latest approaches to ICA problems, including an investigation into certain "hard problems" for the very first time. Comprising contributions from the most respected and innovative researchers in the field, this volume will be of interest to students and researchers in computer science and electrical engineering; research and development personnel in disciplines such as statistical modelling and data analysis; bio-informatic workers; and physicists and chemists requiring novel data analysis methods.

Source Separation and Machine Learning

Source Separation and Machine Learning
  • Author : Jen-Tzung Chien
  • Publisher :Unknown
  • Release Date :2018-11-01
  • Total pages :384
  • ISBN : 9780128045770
GET BOOK HERE

Summary : 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

Advances in Machine Learning

Advances in Machine Learning
  • Author : Zhi-Hua Zhou,Takashi Washio
  • Publisher :Unknown
  • Release Date :2009-10-06
  • Total pages :413
  • ISBN : 9783642052231
GET BOOK HERE

Summary : The First Asian Conference on Machine Learning (ACML 2009) was held at Nanjing, China during November 2–4, 2009.This was the ?rst edition of a series of annual conferences which aim to provide a leading international forum for researchers in machine learning and related ?elds to share their new ideas and research ?ndings. This year we received 113 submissions from 18 countries and regions in Asia, Australasia, Europe and North America. The submissions went through a r- orous double-blind reviewing process. Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews. Each submission was handled by an Area Chair who coordinated discussions among reviewers and made recommendation on the submission. The Program Committee Chairs examined the reviews and meta-reviews to further guarantee the reliability and integrity of the reviewing process. Twenty-nine - pers were selected after this process. To ensure that important revisions required by reviewers were incorporated into the ?nal accepted papers, and to allow submissions which would have - tential after a careful revision, this year we launched a “revision double-check” process. In short, the above-mentioned 29 papers were conditionally accepted, and the authors were requested to incorporate the “important-and-must”re- sionssummarizedbyareachairsbasedonreviewers’comments.Therevised?nal version and the revision list of each conditionally accepted paper was examined by the Area Chair and Program Committee Chairs. Papers that failed to pass the examination were ?nally rejected.

Advances in E-Learning: Experiences and Methodologies

Advances in E-Learning: Experiences and Methodologies
  • Author : Garc¡a-Pe¤alvo, Francisco Jos‚
  • Publisher :Unknown
  • Release Date :2008-03-31
  • Total pages :420
  • ISBN : 9781599047584
GET BOOK HERE

Summary : Web-based training, known as e-learning, has experienced a great evolution and growth in recent years, as the capacity for education is no longer limited by physical and time constraints. The emergence of such a prized learning tool mandates a comprehensive evaluation of the effectiveness and implications of e-learning. Advances in E-Learning: Experiences and Methodologies explores the technical, pedagogical, methodological, tutorial, legal, and emotional aspects of e-learning, considering and analyzing its different application contexts, and providing researchers and practitioners with an innovative view of e-learning as a lifelong learning tool for scholars in both academic and professional spheres.

Independent Component Analysis

Independent Component Analysis
  • Author : Aapo Hyvärinen,Juha Karhunen,Erkki Oja
  • Publisher :Unknown
  • Release Date :2004-04-05
  • Total pages :504
  • ISBN : 9780471464198
GET BOOK HERE

Summary : A comprehensive introduction to ICA for students andpractitioners Independent Component Analysis (ICA) is one of the most excitingnew topics in fields such as neural networks, advanced statistics,and signal processing. This is the first book to provide acomprehensive introduction to this new technique complete with thefundamental mathematical background needed to understand andutilize it. It offers a general overview of the basics of ICA,important solutions and algorithms, and in-depth coverage of newapplications in image processing, telecommunications, audio signalprocessing, and more. Independent Component Analysis is divided into four sections thatcover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for theircontributions to the development of ICA and here cover all therelevant theory, new algorithms, and applications in variousfields. Researchers, students, and practitioners from a variety ofdisciplines will find this accessible volume both helpful andinformative.

Statistical Learning and Pattern Analysis for Image and Video Processing

Statistical Learning and Pattern Analysis for Image and Video Processing
  • Author : Nanning Zheng,Jianru Xue
  • Publisher :Unknown
  • Release Date :2009-07-25
  • Total pages :365
  • ISBN : 9781848823129
GET BOOK HERE

Summary : Why are We Writing This Book? Visual data (graphical, image, video, and visualized data) affect every aspect of modern society. The cheap collection, storage, and transmission of vast amounts of visual data have revolutionized the practice of science, technology, and business. Innovations from various disciplines have been developed and applied to the task of designing intelligent machines that can automatically detect and exploit useful regularities (patterns) in visual data. One such approach to machine intelligence is statistical learning and pattern analysis for visual data. Over the past two decades, rapid advances have been made throughout the ?eld of visual pattern analysis. Some fundamental problems, including perceptual gro- ing,imagesegmentation, stereomatching, objectdetectionandrecognition,and- tion analysis and visual tracking, have become hot research topics and test beds in multiple areas of specialization, including mathematics, neuron-biometry, and c- nition. A great diversity of models and algorithms stemming from these disciplines has been proposed. To address the issues of ill-posed problems and uncertainties in visual pattern modeling and computing, researchers have developed rich toolkits based on pattern analysis theory, harmonic analysis and partial differential eq- tions, geometry and group theory, graph matching, and graph grammars. Among these technologies involved in intelligent visual information processing, statistical learning and pattern analysis is undoubtedly the most popular and imp- tant approach, and it is also one of the most rapidly developing ?elds, with many achievements in recent years. Above all, it provides a unifying theoretical fra- work for intelligent visual information processing applications.

Neural Networks and Learning Machines

Neural Networks and Learning Machines
  • Author : Simon S. Haykin
  • Publisher :Unknown
  • Release Date :2009
  • Total pages :906
  • ISBN : 9780131471399
GET BOOK HERE

Summary : For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Neural Networks and Learning Machines, Third Edition is renowned for its thoroughness and readability. This well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. This is ideal for professional engineers and research scientists. Matlab codes used for the computer experiments in the text are available for download at: http://www.pearsonhighered.com/haykin/ Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.

Artificial Neural Networks and Machine Learning - ICANN 2011

Artificial Neural Networks and Machine Learning - ICANN 2011
  • Author : Timo Honkela,Włodzisław Duch,Mark Girolami,Samuel Kaski
  • Publisher :Unknown
  • Release Date :2011-06-14
  • Total pages :474
  • ISBN : 9783642217371
GET BOOK HERE

Summary : This two volume set (LNCS 6791 and LNCS 6792) constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.

Journal of Machine Learning Research

Journal of Machine Learning Research
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2007
  • Total pages :229
  • ISBN : UCSD:31822036045433
GET BOOK HERE

Summary :

Advances in Neural Networks - ISNN 2006

Advances in Neural Networks - ISNN 2006
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2006
  • Total pages :4288
  • ISBN : 9783540344827
GET BOOK HERE

Summary :

Advances in Neural Networks - ISNN 2005

Advances in Neural Networks - ISNN 2005
  • Author : Jun Wang,Xiaofeng Liao
  • Publisher :Unknown
  • Release Date :2005-05-17
  • Total pages :1055
  • ISBN : 9783540259121
GET BOOK HERE

Summary : This book and its sister volumes constitute the proceedings of the 2nd International Symposium on Neural Networks (ISNN 2005). ISNN 2005 was held in the beautiful mountain city Chongqing by the upper Yangtze River in southwestern China during May 30-June 1, 2005, as a sequel of ISNN 2004 successfully held in Dalian, China. ISNN emerged as a leading conference on neural computation in the region with - creasing global recognition and impact. ISNN 2005 received 1425 submissions from authors on ?ve continents (Asia, Europe, North America, South America, and Oc- nia), 33 countries and regions (Mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, India, Nepal, Iran, Qatar, United Arab Emirates, Turkey, Lithuania, Hungary, Poland, Austria, Switzerland, Germany, France, Sweden, Norway, Spain, Portugal, UK, USA, Canada, Venezuela, Brazil, Chile, Australia, and New Zealand). Based on rigorous reviews, 483 high-quality papers were selected by the Program Committee for presentation at ISNN 2005 and publication in the proce- ings, with an acceptance rate of less than 34%. In addition to the numerous contributed papers, 10 distinguished scholars were invited to give plenary speeches and tutorials at ISNN 2005.

Advances in Neural Networks--ISNN ...

Advances in Neural Networks--ISNN ...
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2005
  • Total pages :229
  • ISBN : UOM:39015058761803
GET BOOK HERE

Summary :

Advances in Neural Information Processing Systems 12

Advances in Neural Information Processing Systems 12
  • Author : Sara A. Solla,Todd K. Leen,Klaus-Robert Müller
  • Publisher :Unknown
  • Release Date :2000
  • Total pages :1080
  • ISBN : 0262194503
GET BOOK HERE

Summary : The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Advances in Financial Machine Learning

Advances in Financial Machine Learning
  • Author : Marcos Lopez de Prado
  • Publisher :Unknown
  • Release Date :2018-01-23
  • Total pages :400
  • ISBN : 9781119482116
GET BOOK HERE

Summary : Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Handbook of Computational Intelligence in Manufacturing and Production Management

Handbook of Computational Intelligence in Manufacturing and Production Management
  • Author : Laha, Dipak,Mandal, Purnendu
  • Publisher :Unknown
  • Release Date :2007-11-30
  • Total pages :516
  • ISBN : 9781599045849
GET BOOK HERE

Summary : During the last two decades, computer and information technologies have forced great changes in the ways businesses manage operations in meeting the desired quality of products and services, customer demands, competition, and other challenges. The Handbook of Computational Intelligence in Manufacturing and Production Management focuses on new developments in computational intelligence in areas such as forecasting, scheduling, production planning, inventory control, and aggregate planning, among others. This comprehensive collection of research provides cutting-edge knowledge on information technology developments for both researchers and professionals in fields such as operations and production management, Web engineering, artificial intelligence, and information resources management.

Machine Learning for Audio, Image and Video Analysis

Machine Learning for Audio, Image and Video Analysis
  • Author : Francesco Camastra,Alessandro Vinciarelli
  • Publisher :Unknown
  • Release Date :2015-07-21
  • Total pages :561
  • ISBN : 9781447167358
GET BOOK HERE

Summary : This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.