Download or read book Parallel Testings and Variable Selection written by Haim Yehuda Bar and published by . This book was released on 2012 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop efficient and powerful statistical methods for high-dimensional data, where the sample size is much smaller than the number of features (the so-called 'large p, small n' problem). We deal with three important problems. First, we develop a mixture-model approach for parallel testing for unequal variances in two-sample experiments. The treatment effect on the variance has received little attention in the statistical literature, which so far focused mostly on the effect on the mean. The effect on the variance is increasingly recognized in recent biological literature, and we develop an empirical Bayes approach for testing differences in variance when the number of tests is large. We show that the model is useful in a wide range of applications, that our method is much more powerful than traditional tests for unequal variances, and that it is robust to the normality assumption. Second, we extend these ideas and develop a novel bivariate normal model that tests for both differential expression and differential variation between the two groups. We show in simulations that this new method yields a substantial gain in power when differential variation is present. Through a three-step estimation approach, in which we apply the Laplace approximation and the EM algorithm, we get a computationally efficient method, which is particularly well-suited for 'large p, small n' situations. Third, we deal with the problem of variable selection where the number of putative variables is large, possibly much larger than the sample size. We develop a model-based, empirical Bayes approach. By treating the putative variables as random effects, we get shrinkage estimation, which results in increased power and significantly faster convergence, compared with simulation-based methods. Furthermore, we employ computational tricks which allow us to increase the speed of our algorithm, to handle a very large number of putative variables, and to control the multicollinearity in the model. The motivation for developing this approach is QTL analysis, but our method is applicable to a broad range of applications. We use two widely-studied data sets, and show that our model selection algorithm yields excellent results.
Download or read book Parallel Execution of Parlog written by Andrew Cheese and published by Springer Science & Business Media. This book was released on 1992-05-20 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph concentrates on the implementation of concurrent logic programming languages on loosely-coupled parallel computer architectures. Two different abstract models are also considered: a graph reduction based model and a more imperative approach. The design of a specialized instruction set is presented that is general enough to be used for the whole family of concurrent logic programming languages. In particular the language Parlog is concentrated upon because it is the most efficiently implementable of all the non-flat logic programming languages. Other issues arising from the implementation of a programming language are discussed, in particular the design of a load balancing scheme which deals with the large number of short-lived processes inherent in a correct language implementation. Detailed descriptions of all the data structures and synchronisation algorithms are also presented. Resource exhaustion is also discussed and handled within the implementations. Detailed performance results for both models of computation are given. From the material it should be possible for the reader to create an implementation.
Download or read book Handbook of Parallel Constraint Reasoning written by Youssef Hamadi and published by Springer. This book was released on 2018-04-05 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book presenting a broad overview of parallelism in constraint-based reasoning formalisms. In recent years, an increasing number of contributions have been made on scaling constraint reasoning thanks to parallel architectures. The goal in this book is to overview these achievements in a concise way, assuming the reader is familiar with the classical, sequential background. It presents work demonstrating the use of multiple resources from single machine multi-core and GPU-based computations to very large scale distributed execution platforms up to 80,000 processing units. The contributions in the book cover the most important and recent contributions in parallel propositional satisfiability (SAT), maximum satisfiability (MaxSAT), quantified Boolean formulas (QBF), satisfiability modulo theory (SMT), theorem proving (TP), answer set programming (ASP), mixed integer linear programming (MILP), constraint programming (CP), stochastic local search (SLS), optimal path finding with A*, model checking for linear-time temporal logic (MC/LTL), binary decision diagrams (BDD), and model-based diagnosis (MBD). The book is suitable for researchers, graduate students, advanced undergraduates, and practitioners who wish to learn about the state of the art in parallel constraint reasoning.
Download or read book Euro Par 2005 Parallel Processing written by José C. Cunha and published by Springer Science & Business Media. This book was released on 2005-08-18 with total page 1311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Euro-Par 2005 was the eleventh conference in the Euro-Par series. It was organized by the Centre for Informatics and Information Technology (CITI) and the Department of Informatics of the Faculty of Science and Technology of Universidade Nova de Lisboa, at the Campus of Monte de Caparica.
Download or read book Computational Science and Its Applications ICCSA 2013 written by Beniamino Murgante and published by Springer. This book was released on 2013-06-22 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five-volume set LNCS 7971-7975 constitutes the refereed proceedings of the 13th International Conference on Computational Science and Its Applications, ICCSA 2013, held in Ho Chi Minh City, Vietnam, in June 2013. Apart from the general track, ICCSA 2013 also include 33 special sessions and workshops, in various areas of computational sciences, ranging from computational science technologies, to specific areas of computational sciences, such as computer graphics and virtual reality. There are 46 papers from the general track, and 202 in special sessions and workshops.
Download or read book Parallel Execution of Logic Programs written by John S. Conery and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an updated version of my Ph.D. dissertation, The AND/OR Process Model for Parallel Interpretation of Logic Programs. The three years since that paper was finished (or so I thought then) have seen quite a bit of work in the area of parallel execution models and programming languages for logic programs. A quick glance at the bibliography here shows roughly 50 papers on these topics, 40 of which were published after 1983. The main difference between the book and the dissertation is the updated survey of related work. One of the appendices in the dissertation was an overview of a Prolog implementation of an interpreter based on the AND/OR Process Model, a simulator I used to get some preliminary measurements of parallelism in logic programs. In the last three years I have been involved with three other implementations. One was written in C and is now being installed on a small multiprocessor at the University of Oregon. Most of the programming of this interpreter was done by Nitin More under my direction for his M.S. project. The other two, one written in Multilisp and the other in Modula-2, are more limited, intended to test ideas about implementing specific aspects of the model. Instead of an appendix describing one interpreter, this book has more detail about implementation included in Chapters 5 through 7, based on a combination of ideas from the four interpreters.
Download or read book Python Feature Engineering Cookbook written by Soledad Galli and published by Packt Publishing Ltd. This book was released on 2022-10-31 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create end-to-end, reproducible feature engineering pipelines that can be deployed into production using open-source Python libraries Key Features Learn and implement feature engineering best practices Reinforce your learning with the help of multiple hands-on recipes Build end-to-end feature engineering pipelines that are performant and reproducible Book DescriptionFeature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to use open source Python libraries to accelerate the process via a plethora of practical, hands-on recipes. This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers. The concluding chapters show you how to develop new features from various types of data, including text, time series, and relational databases. With the help of numerous open source Python libraries, you'll learn how to implement each feature engineering method in a performant, reproducible, and elegant manner. By the end of this Python book, you will have the tools and expertise needed to confidently build end-to-end and reproducible feature engineering pipelines that can be deployed into production.What you will learn Impute missing data using various univariate and multivariate methods Encode categorical variables with one-hot, ordinal, and count encoding Handle highly cardinal categorical variables Transform, discretize, and scale your variables Create variables from date and time with pandas and Feature-engine Combine variables into new features Extract features from text as well as from transactional data with Featuretools Create features from time series data with tsfresh Who this book is for This book is for machine learning and data science students and professionals, as well as software engineers working on machine learning model deployment, who want to learn more about how to transform their data and create new features to train machine learning models in a better way.
Download or read book Official Gazette of the United States Patent and Trademark Office written by and published by . This book was released on 1993 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Knowledge Discovery and Data Mining written by Wee Keong Ng and published by Springer. This book was released on 2006-03-10 with total page 902 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2006, held in Singapore in April 2006. The 67 revised full papers and 33 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 501 submissions. The papers are organized in topical sections on Classification, Ensemble Learning, Clustering, Support Vector Machines, Text and Document Mining, Web Mining, Bio-Data Mining, and more.
Download or read book Scaling Up Machine Learning written by Ron Bekkerman and published by Cambridge University Press. This book was released on 2012 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
Download or read book Practical Parallel Programming written by Barr E. Bauer and published by Academic Press. This book was released on 2014-06-28 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the book that will teach programmers to write faster, more efficient code for parallel processors. The reader is introduced to a vast array of procedures and paradigms on which actual coding may be based. Examples and real-life simulations using these devices are presented in C and FORTRAN.
Download or read book Sequential Multiple Testing for Variable Selection in High Dimensional Linear Model written by Hailu Chen and published by . This book was released on 2016 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covariance test is proposed for testing the significance of the predictor variable that enters the current lasso model along the lasso solution path. In this paper, we propose the sequential multiple testing structure using covariance test p-values, which has good power properties with error rate controlled at a desired level. Specifically, we consider the full underlying hypotheses and the error rate control within each step as well as across all steps along the lasso solution path.
Download or read book Alternative Methods of Variable Selection in Linear Regression Models for Incomplete Multivariate Normal Data written by Xiaowei Yang and published by . This book was released on 2002 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Neural Networks and Machine Learning ICANN 2019 Deep Learning written by Igor V. Tetko and published by Springer Nature. This book was released on 2019-09-09 with total page 807 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Download or read book Emerging Trends in Intelligent and Interactive Systems and Applications written by Madjid Tavana and published by Springer Nature. This book was released on 2020-12-17 with total page 1007 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the proceeding of the 5th International Conference on Intelligent, Interactive Systems and Applications (IISA 2020), held in Shanghai, China, on September 25–27, 2020. The IISA proceedings, with the latest scientific findings, and methods for solving intriguing problems, are a reference for state-of-the-art works on intelligent and interactive systems. This book covers nine interesting and current topics on different systems’ orientations, including Analytical Systems, Database Management Systems, Electronics Systems, Energy Systems, Intelligent Systems, Network Systems, Optimization Systems, and Pattern Recognition Systems and Applications. The chapters included in this book cover significant recent developments in the field, both in terms of theoretical foundations and their practical application. An important characteristic of the works included here is the novelty of the solution approaches to the most interesting applications of intelligent and interactive systems.
Download or read book The University of Michigan Statistical Program Census written by and published by UM Libraries. This book was released on 1974 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parallel Architectures and Bioinspired Algorithms written by Francisco Fernández de Vega and published by Springer. This book was released on 2012-04-27 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents examples of best practices when combining bioinspired algorithms with parallel architectures. The book includes recent work by leading researchers in the field and offers a map with the main paths already explored and new ways towards the future. Parallel Architectures and Bioinspired Algorithms will be of value to both specialists in Bioinspired Algorithms, Parallel and Distributed Computing, as well as computer science students trying to understand the present and the future of Parallel Architectures and Bioinspired Algorithms.
