1.

Record Nr.

UNISA996466325903316

Titolo

Artificial Neural Networks and Machine Learning – ICANN 2018 [[electronic resource] ] : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III / / edited by Věra Kůrková, Yannis Manolopoulos, Barbara Hammer, Lazaros Iliadis, Ilias Maglogiannis

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018

ISBN

3-030-01424-X

Edizione

[1st ed. 2018.]

Descrizione fisica

1 online resource (XXIX, 846 p. 311 illus.)

Collana

Theoretical Computer Science and General Issues, , 2512-2029 ; ; 11141

Disciplina

006.32

Soggetti

Artificial intelligence

Computer vision

Computer engineering

Computer networks

Data protection

Algorithms

Artificial Intelligence

Computer Vision

Computer Engineering and Networks

Computer Communication Networks

Data and Information Security

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Sommario/riassunto

This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State



Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning.



2.

Record Nr.

UNINA9910164975703321

Autore

Reader Capitol

Titolo

Summary of Flying High

Pubbl/distr/stampa

Cork, : Primento Digital, 2013

ISBN

9782511000786

2511000784

Descrizione fisica

1 online resource (21 p.)

Disciplina

928.1092834

Soggetti

Conservatism - United States

Third parties (United States politics)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di contenuto

Title page; Book Presentation; Book Abstract; About the Author; Important Note About This Ebook; Summary of Flying High (William F. Buckley, Jr.); Stirrings in Chicago; A Figure in the Shadows; The Conservative Bible; Building a National Reputation; The Campaign Begins; A Turning Point; After California; Dissent in San Francisco; "Extremism" is Always a Bad Word; The Ghost of JFK; The Eve of Disaster; Reagan: A Fresh Star; Reflection; Later Years; Buy the Book; About the Summary Publisher; Copyright

Sommario/riassunto

This ebook consists of a summary of the ideas, viewpoints and facts presented by William F. Buckley, Jr. in his book "Flying High: Remembering Barry Goldwater". This summary offers a concise overview of the entire book in less than 30 minutes reading time. However this work does not replace in any case William F. Buckley's, Jr. book.<br>Buckley recalls the success and the mistakes made during the Goldwater quest for the White House. <br>



3.

Record Nr.

UNINA9910733728903321

Autore

Saikia Hemanta

Titolo

Cricket Performance Management : Mathematical Formulation and Analytics / / by Hemanta Saikia, Dibyojyoti Bhattacharjee, Diganta Mukherjee

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019

ISBN

981-15-1354-6

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (246 pages)

Collana

Indian Statistical Institute Series, , 2523-3114

Disciplina

796.358092

Soggetti

Statistics

Popular Science in Statistics

Statistics, general

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Chapter 1. Cricket, Statistics and Data Mining -- Chapter 2. Franchisee Cricket and Cricketer’s Auction -- Chapter 3. Quantifying Performance of Cricketers -- Chapter 4. Fielding Performance Measure: Issues, Concern and Solution -- Chapter 5. Performance Based Market Valuation of Players -- Chapter 6. Impact of Age on Performance of Cricketers -- Chapter 7. Performing Under Difficulty: The Magical Pressure Index -- Chapter 8. Decision Making Approaches to Optimum Team Selection.

Sommario/riassunto

This book focuses on the application of data mining techniques in cricket. It provides detailed examples of how data mining can be helpful for decision-making in sports with special reference to cricket, particularly the quantitative features related to Twenty20 cricket, the latest and the most popular format of the game. The book highlights the performance quantification of cricketers (batsmen, bowlers, all-rounders, and wicket keepers), determining the market valuation of cricketers based on their on-field performances and the effect of age on the performance of the cricketers. It also provides a comprehensive overview of the different aspects of the game where quantitative techniques are beneficial, and highlights the use of statistical and data mining tools in analysing sports-related data and objective decision-



making in sports. The book appeals to a wide readership, including postgraduate students of statistics/mathematics, data analysts, sports management bodies. It also offers data miners, such as researchers in statistics, mathematics, operations research, and computer science ideas for projects.