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Author : Regina Y. Liu
Publisher : IMS
ISBN 13 : 9780940600706
Total Pages : 286 pages
Book Rating : 4.06/5 ( download)
Download or read book Complex Datasets and Inverse Problems written by Regina Y. Liu and published by IMS. This book was released on 2007 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jing Qin
Publisher : Springer
ISBN 13 : 9811048568
Total Pages : 624 pages
Book Rating : 4.62/5 ( download)
Download or read book Biased Sampling, Over-identified Parameter Problems and Beyond written by Jing Qin and published by Springer. This book was released on 2017-06-14 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others.
Author : S. Ejaz Ahmed
Publisher : Springer
ISBN 13 : 3319415735
Total Pages : 386 pages
Book Rating : 4.34/5 ( download)
Download or read book Big and Complex Data Analysis written by S. Ejaz Ahmed and published by Springer. This book was released on 2017-03-21 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.
Author : Petra Perner
Publisher : Springer
ISBN 13 : 331941920X
Total Pages : 807 pages
Book Rating : 4.06/5 ( download)
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2016-06-27 with total page 807 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, held in New York, NY, USA in July 2016. The 58 regular papers presented in this book were carefully reviewed and selected from 169 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Author : Josep Domingo-Ferrer
Publisher : Springer
ISBN 13 : 3540874712
Total Pages : 346 pages
Book Rating : 4.13/5 ( download)
Download or read book Privacy in Statistical Databases written by Josep Domingo-Ferrer and published by Springer. This book was released on 2008-09-22 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Privacy in statistical databases is a discipline whose purpose is to provide solutions to the tension between the increasing social, political and economical demand of accurate information, and the legal and ethical obligation to protect the privacy of the various parties involved. Those parties are the respondents (the individuals and enterprises to which the database records refer), the data owners (those organizations spending money in data collection) and the users (the ones querying the database, who would like their queries to stay con?d- tial). Beyond law and ethics, there are also practical reasons for data collecting agencies to invest in respondent privacy: if individual respondents feel their p- vacyguaranteed,they arelikelyto providemoreaccurateresponses. Data owner privacy is primarily motivated by practical considerations: if an enterprise c- lects data at its own expense, it may wish to minimize leakage of those data to other enterprises (even to those with whom joint data exploitation is planned). Finally, user privacy results in increased user satisfaction, even if it may curtail the ability of the database owner to pro?le users. Thereareatleasttwotraditionsinstatisticaldatabaseprivacy,bothofwhich started in the 1970s: one stems from o?cial statistics, where the discipline is also known as statistical disclosure control (SDC), and the other originatesfrom computer science and database technology. In o?cial statistics, the basic c- cern is respondent privacy.
Author : David L. Banks
Publisher : CRC Press
ISBN 13 : 1000096068
Total Pages : 571 pages
Book Rating : 4.64/5 ( download)
Download or read book Handbook of Forensic Statistics written by David L. Banks and published by CRC Press. This book was released on 2020-11-05 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Forensic Statistics is a collection of chapters by leading authorities in forensic statistics. Written for statisticians, scientists, and legal professionals having a broad range of statistical expertise, it summarizes and compares basic methods of statistical inference (frequentist, likelihoodist, and Bayesian) for trace and other evidence that links individuals to crimes, the modern history and key controversies in the field, and the psychological and legal aspects of such scientific evidence. Specific topics include uncertainty in measurements and conclusions; statistically valid statements of weight of evidence or source conclusions; admissibility and presentation of statistical findings; and the state of the art of methods (including problems and pitfalls) for collecting, analyzing, and interpreting data in such areas as forensic biology, chemistry, and pattern and impression evidence. The particular types of evidence that are discussed include DNA, latent fingerprints, firearms and toolmarks, glass, handwriting, shoeprints, and voice exemplars.
Author : Alexander Gammerman
Publisher : Springer
ISBN 13 : 331933395X
Total Pages : 229 pages
Book Rating : 4.53/5 ( download)
Download or read book Conformal and Probabilistic Prediction with Applications written by Alexander Gammerman and published by Springer. This book was released on 2016-04-16 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in Madrid, Spain, in April 2016. The 14 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 23 submissions and cover topics on theory of conformal prediction; applications of conformal prediction; and machine learning.
Author : Tore Schweder
Publisher : Cambridge University Press
ISBN 13 : 0521861608
Total Pages : 521 pages
Book Rating : 4.01/5 ( download)
Download or read book Confidence, Likelihood, Probability written by Tore Schweder and published by Cambridge University Press. This book was released on 2016-02-24 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.
Author : Yunqian Ma
Publisher : CRC Press
ISBN 13 : 1466558873
Total Pages : 410 pages
Book Rating : 4.78/5 ( download)
Download or read book Manifold Learning Theory and Applications written by Yunqian Ma and published by CRC Press. This book was released on 2011-12-20 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations. Manifold learning, a groundbreaking technique designed to tackle these issues of dimensionality reduction, finds widespread
Author : Aris Gkoulalas-Divanis
Publisher : Springer
ISBN 13 : 3319236334
Total Pages : 832 pages
Book Rating : 4.39/5 ( download)
Download or read book Medical Data Privacy Handbook written by Aris Gkoulalas-Divanis and published by Springer. This book was released on 2015-11-26 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook covers Electronic Medical Record (EMR) systems, which enable the storage, management, and sharing of massive amounts of demographic, diagnosis, medication, and genomic information. It presents privacy-preserving methods for medical data, ranging from laboratory test results to doctors’ comments. The reuse of EMR data can greatly benefit medical science and practice, but must be performed in a privacy-preserving way according to data sharing policies and regulations. Written by world-renowned leaders in this field, each chapter offers a survey of a research direction or a solution to problems in established and emerging research areas. The authors explore scenarios and techniques for facilitating the anonymization of different types of medical data, as well as various data mining tasks. Other chapters present methods for emerging data privacy applications and medical text de-identification, including detailed surveys of deployed systems. A part of the book is devoted to legislative and policy issues, reporting on the US and EU privacy legislation and the cost of privacy breaches in the healthcare domain. This reference is intended for professionals, researchers and advanced-level students interested in safeguarding medical data.
