Learning In The Absence Of Training Data

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Learning in the Absence of Training Data

Author : Dalia Chakrabarty
Publisher : Springer Nature
ISBN 13 : 303131011X
Total Pages : 241 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Learning in the Absence of Training Data by : Dalia Chakrabarty

Download or read book Learning in the Absence of Training Data written by Dalia Chakrabarty and published by Springer Nature. This book was released on 2023-07-13 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the concept of “bespoke learning”, a new mechanistic approach that makes it possible to generate values of an output variable at each designated value of an associated input variable. Here the output variable generally provides information about the system’s behaviour/structure, and the aim is to learn the input-output relationship, even though little to no information on the output is available, as in multiple real-world problems. Once the output values have been bespoke-learnt, the originally-absent training set of input-output pairs becomes available, so that (supervised) learning of the sought inter-variable relation is then possible. Three ways of undertaking such bespoke learning are offered: by tapping into system dynamics in generic dynamical systems, to learn the function that causes the system’s evolution; by comparing realisations of a random graph variable, given multivariate time series datasets of disparate temporal coverage; and by designing maximally information-availing likelihoods in static systems. These methodologies are applied to four different real-world problems: forecasting daily COVID-19 infection numbers; learning the gravitational mass density in a real galaxy; learning a sub-surface material density function; and predicting the risk of onset of a disease following bone marrow transplants. Primarily aimed at graduate and postgraduate students studying a field which includes facets of statistical learning, the book will also benefit experts working in a wide range of applications. The prerequisites are undergraduate level probability and stochastic processes, and preliminary ideas on Bayesian statistics.

Bayesian Statistics and New Generations

Author : Raffaele Argiento
Publisher : Springer Nature
ISBN 13 : 3030306119
Total Pages : 184 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Bayesian Statistics and New Generations by : Raffaele Argiento

Download or read book Bayesian Statistics and New Generations written by Raffaele Argiento and published by Springer Nature. This book was released on 2019-11-21 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.

BASICS OF MACHINE LEARNING, DEEP LEARNING AND NATURAL LANGUAGE PROCESSING

Author : Dr.R.GNANAJEYARAMAN
Publisher : SK Research Group of Companies
ISBN 13 : 8119980751
Total Pages : 217 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis BASICS OF MACHINE LEARNING, DEEP LEARNING AND NATURAL LANGUAGE PROCESSING by : Dr.R.GNANAJEYARAMAN

Download or read book BASICS OF MACHINE LEARNING, DEEP LEARNING AND NATURAL LANGUAGE PROCESSING written by Dr.R.GNANAJEYARAMAN and published by SK Research Group of Companies. This book was released on 2024-02-07 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.R.GNANAJEYARAMAN, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.U.ARUL, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.M.RAMA MOORTHY, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.CARMEL MARY BELINDA.M.J, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.

The Science of Citizen Science

Author : Katrin Vohland
Publisher : Springer Nature
ISBN 13 : 3030582787
Total Pages : 520 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis The Science of Citizen Science by : Katrin Vohland

Download or read book The Science of Citizen Science written by Katrin Vohland and published by Springer Nature. This book was released on 2021 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book discusses how the involvement of citizens into scientific endeavors is expected to contribute to solve the big challenges of our time, such as climate change and the loss of biodiversity, growing inequalities within and between societies, and the sustainability turn. The field of citizen science has been growing in recent decades. Many different stakeholders from scientists to citizens and from policy makers to environmental organisations have been involved in its practice. In addition, many scientists also study citizen science as a research approach and as a way for science and society to interact and collaborate. This book provides a representation of the practices as well as scientific and societal outcomes in different disciplines. It reflects the contribution of citizen science to societal development, education, or innovation and provides and overview of the field of actors as well as on tools and guidelines. It serves as an introduction for anyone who wants to get involved in and learn more about the science of citizen science.

Machine Learning

Author : T V Geetha
Publisher : CRC Press
ISBN 13 : 1000867161
Total Pages : 478 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Machine Learning by : T V Geetha

Download or read book Machine Learning written by T V Geetha and published by CRC Press. This book was released on 2023-05-17 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms – When to use them & Why – for Application developers and Researchers Machine Learning from an Application Perspective – General & Machine learning for Healthcare, Education, Business, Engineering Applications Ethics of machine learning including Bias, Fairness, Trust, Responsibility Basics of Deep learning, important deep learning models and applications Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.

Quantitative Investment Analysis, Workbook

Author : CFA Institute
Publisher : John Wiley & Sons
ISBN 13 : 1119743672
Total Pages : 288 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Quantitative Investment Analysis, Workbook by : CFA Institute

Download or read book Quantitative Investment Analysis, Workbook written by CFA Institute and published by John Wiley & Sons. This book was released on 2020-09-23 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thoroughly revised and updated fourth edition of the companion workbook to Quantitative Investment Analysis is here. Now in its fourth edition, the Quantitative Investment Analysis Workbook offers a range of practical information and exercises that will facilitate your mastery of quantitative methods and their application in today's investment process. Part of the reputable CFA Institute Investment Series, the workbook is designed to further your hands-on experience with a variety of learning outcomes, summary overview sections, and challenging problems and solutions. The workbook provides all the statistical tools and latest information to help you become a confident and knowledgeable investor, including expanded problems on Machine Learning algorithms and the role of Big Data in investment contexts. Well suited for motivated individuals who learn on their own, as well as a general reference, this companion resource delivers a clear, example-driven method for practicing the tools and techniques covered in the primary Quantitative Investment Analysis, 4th Edition text.?? Inside you'll find information and exercises to help you: Work real-world problems associated with the modern quantitative investment process Master visualizing and summarizing data Review the fundamentals of single linear and multiple linear regression Use multifactor models Measure and manage market risk effectively In both the workbook and the primary Quantitative Investment Analysis, 4th Edition text, the authors go to great lengths to ensure an even treatment of subject matter, consistency of mathematical notation, and continuity of topic coverage that is critical to the learning process. For everyone who requires a streamlined route to mastering quantitative methods in investments, Quantitative Investment Analysis Workbook, 4th Edition offers world-class practice based on actual scenarios faced by professionals every day.

Artificial Neural Networks as Models of Neural Information Processing

Author : Marcel van Gerven
Publisher : Frontiers Media SA
ISBN 13 : 2889454010
Total Pages : 220 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Artificial Neural Networks as Models of Neural Information Processing by : Marcel van Gerven

Download or read book Artificial Neural Networks as Models of Neural Information Processing written by Marcel van Gerven and published by Frontiers Media SA. This book was released on 2018-02-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.

Explainable Machine Learning for Multimedia Based Healthcare Applications

Author : M. Shamim Hossain
Publisher : Springer Nature
ISBN 13 : 3031380363
Total Pages : 240 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Explainable Machine Learning for Multimedia Based Healthcare Applications by : M. Shamim Hossain

Download or read book Explainable Machine Learning for Multimedia Based Healthcare Applications written by M. Shamim Hossain and published by Springer Nature. This book was released on with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Hybrid Artificial Intelligent Systems

Author : Emilio S. Corchado Rodriguez
Publisher : Springer
ISBN 13 : 3642289312
Total Pages : 636 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Hybrid Artificial Intelligent Systems by : Emilio S. Corchado Rodriguez

Download or read book Hybrid Artificial Intelligent Systems written by Emilio S. Corchado Rodriguez and published by Springer. This book was released on 2012-03-15 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining: data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations.

2022 CFA Program Curriculum Level II Box Set

Author : CFA Institute
Publisher : John Wiley & Sons
ISBN 13 : 111970507X
Total Pages : 608 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis 2022 CFA Program Curriculum Level II Box Set by : CFA Institute

Download or read book 2022 CFA Program Curriculum Level II Box Set written by CFA Institute and published by John Wiley & Sons. This book was released on 2021-05-20 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepare for success on the 2022 CFA Level II exam with the latest official CFA® Program Curriculum. The 2022 CFA Program Curriculum Level II Box Set contains all the material you need to succeed on the Level II CFA exam in 2022. This set includes the full official curriculum for Level II and is part of the larger CFA Candidate Body of Knowledge (CBOK). Organized to get you accustomed to the exam’s heavy reliance on vignettes, the Level II curriculum will help you master mini case studies and accompanying analyses. Highly visual and intuitively organized, this box set allows you to: Learn from financial thought leaders. Access market-relevant instruction. Gain critical knowledge and skills. The set also includes practice questions to assist with your recall of key terms, concepts, and formulas. Perfect for anyone preparing for the 2022 Level II CFA exam, the 2022 CFA Program Curriculum Level II Box Set is a must-have resource for those seeking the intermediate skills required to become a Chartered Financial Analyst®.

Explanation-Based Neural Network Learning

Author : Sebastian Thrun
Publisher : Springer Science & Business Media
ISBN 13 : 1461313813
Total Pages : 274 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Explanation-Based Neural Network Learning by : Sebastian Thrun

Download or read book Explanation-Based Neural Network Learning written by Sebastian Thrun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. `The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.' From the Foreword by Tom M. Mitchell.

Exploring Malicious Hacker Communities

Author : Ericsson Marin
Publisher : Cambridge University Press
ISBN 13 : 1108870082
Total Pages : 225 pages
Book Rating : 4.1/5 (88 download)

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Book Synopsis Exploring Malicious Hacker Communities by : Ericsson Marin

Download or read book Exploring Malicious Hacker Communities written by Ericsson Marin and published by Cambridge University Press. This book was released on 2021-04-29 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Malicious hackers utilize the World Wide Web to share knowledge. Analyzing the online communication of these threat actors can help reduce the risk of attacks. This book shifts attention from the defender environment to the attacker environment, offering a new security paradigm of 'proactive cyber threat intelligence' that allows defenders of computer networks to gain a better understanding of their adversaries by analyzing assets, capabilities, and interest of malicious hackers. The authors propose models, techniques, and frameworks based on threat intelligence mined from the heart of the underground cyber world: the malicious hacker communities. They provide insights into the hackers themselves and the groups they form dynamically in the act of exchanging ideas and techniques, buying or selling malware, and exploits. The book covers both methodology - a hybridization of machine learning, artificial intelligence, and social network analysis methods - and the resulting conclusions, detailing how a deep understanding of malicious hacker communities can be the key to designing better attack prediction systems.

Deep Learning For Physics Research

Author : Martin Erdmann
Publisher : World Scientific
ISBN 13 : 9811237476
Total Pages : 340 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Deep Learning For Physics Research by : Martin Erdmann

Download or read book Deep Learning For Physics Research written by Martin Erdmann and published by World Scientific. This book was released on 2021-06-25 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.

Knowledge-Based Software Engineering: 2022

Author : Maria Virvou
Publisher : Springer Nature
ISBN 13 : 3031175832
Total Pages : 219 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Knowledge-Based Software Engineering: 2022 by : Maria Virvou

Download or read book Knowledge-Based Software Engineering: 2022 written by Maria Virvou and published by Springer Nature. This book was released on 2023-02-17 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains extended versions of the works and new research results presented at the 14th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022). JCKBSE2022 was originally planned to take place in Larnaca, Cyprus. Unfortunately, the COVID-19 pandemic forced it to be rescheduled as an online conference. JCKBSE is a well-established international biennial conference that focuses on the applications of Artificial Intelligence on Software Engineering. The 14th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022) was organized by the Department of Informatics of the University of Piraeus, Greece. This book is a valuable resource for experts and researchers in the field of (knowledge-based) software engineering. It is also valuable to general readers in the fields of artificial and computational intelligence and, more generally, computer science, wishing to learn more about the exciting field of (knowledge-based) software engineering and its applications. An extensive list of bibliographic references at the end of each chapter helps readers to probe deeper into the application areas of interest to them.

Object Oriented Data Analysis

Author : J. S. Marron
Publisher : CRC Press
ISBN 13 : 1351189662
Total Pages : 436 pages
Book Rating : 4.3/5 (511 download)

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Book Synopsis Object Oriented Data Analysis by : J. S. Marron

Download or read book Object Oriented Data Analysis written by J. S. Marron and published by CRC Press. This book was released on 2021-11-18 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object Oriented Data Analysis is a framework that facilitates inter-disciplinary research through new terminology for discussing the often many possible approaches to the analysis of complex data. Such data are naturally arising in a wide variety of areas. This book aims to provide ways of thinking that enable the making of sensible choices. The main points are illustrated with many real data examples, based on the authors' personal experiences, which have motivated the invention of a wide array of analytic methods. While the mathematics go far beyond the usual in statistics (including differential geometry and even topology), the book is aimed at accessibility by graduate students. There is deliberate focus on ideas over mathematical formulas. J. S. Marron is the Amos Hawley Distinguished Professor of Statistics, Professor of Biostatistics, Adjunct Professor of Computer Science, Faculty Member of the Bioinformatics and Computational Biology Curriculum and Research Member of the Lineberger Cancer Center and the Computational Medicine Program, at the University of North Carolina, Chapel Hill. Ian L. Dryden is a Professor in the Department of Mathematics and Statistics at Florida International University in Miami, has served as Head of School of Mathematical Sciences at the University of Nottingham, and is joint author of the acclaimed book Statistical Shape Analysis.

New Advances in Intelligent Signal Processing

Author : Antonio Ruano
Publisher : Springer
ISBN 13 : 3642117392
Total Pages : 254 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis New Advances in Intelligent Signal Processing by : Antonio Ruano

Download or read book New Advances in Intelligent Signal Processing written by Antonio Ruano and published by Springer. This book was released on 2011-08-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current volume “New Advances in Intelligent Signal Processing” contains extended works based on a careful selection of papers presented originally at the jubilee sixth IEEE International Symposium on Intelligent Signal Processing (WISP’2009), held in Budapest Hungary, August 26-28, 2009 - celebrating the 10 years anniversary of the WISP event series. The present book does not intent to be an overall survey on the fields of interest of the area, but tries to find topics which represent new, hot, and challenging problems. The book begins with papers investigating selected problems of Modeling, Identification, and Clustering such as fuzzy random variables, evolutionary multi-objective neural network models, a structural learning model of neural networks within a Boltzmann machine, a robust DNA-based clustering techniques, and the advances of combining multi-criteria analysis of signals and pattern recognition using machine learning principles. In the second part of the book Image Processing is treated. The carefully edited chapters deal with fuzzy relation based image enhancement, image contrast control technique based on the application of Łukasiewicz algebra operators, low complexity situational models of image quality improvement, flexible representation of map images to quantum computers, and object recognition in images. The last chapter presents an image processing application for elderly care, performing real-time 3D tracking based on a new evaluative multi-modal algorithm.

Computer Vision -- ECCV 2010

Author : Kostas Daniilidis
Publisher : Springer Science & Business Media
ISBN 13 : 364215560X
Total Pages : 836 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Computer Vision -- ECCV 2010 by : Kostas Daniilidis

Download or read book Computer Vision -- ECCV 2010 written by Kostas Daniilidis and published by Springer Science & Business Media. This book was released on 2010-08-30 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising LNCS volumes 6311 until 6313 constitutes the refereed proceedings of the 11th European Conference on Computer Vision, ECCV 2010, held in Heraklion, Crete, Greece, in September 2010. The 325 revised papers presented were carefully reviewed and selected from 1174 submissions. The papers are organized in topical sections on object and scene recognition; segmentation and grouping; face, gesture, biometrics; motion and tracking; statistical models and visual learning; matching, registration, alignment; computational imaging; multi-view geometry; image features; video and event characterization; shape representation and recognition; stereo; reflectance, illumination, color; medical image analysis.