1# Library to Find Best eBook for Read
Author : Rudiyanto Gunawan
Release : 2000
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Dimensionality Reduction and Robustness Analysis of Large Scale Systems by : Rudiyanto Gunawan
Download or read book Dimensionality Reduction and Robustness Analysis of Large Scale Systems written by Rudiyanto Gunawan. This book was released on 2000. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter Benner
Release : 2006-03-30
Genre : Technology & Engineering
Kind : eBook
Book Rating : 091/5 ( reviews)
Book Synopsis Dimension Reduction of Large-Scale Systems by : Peter Benner
Download or read book Dimension Reduction of Large-Scale Systems written by Peter Benner. This book was released on 2006-03-30. Available in PDF, EPUB and Kindle. Book excerpt: In the past decades, model reduction has become an ubiquitous tool in analysis and simulation of dynamical systems, control design, circuit simulation, structural dynamics, CFD, and many other disciplines dealing with complex physical models. The aim of this book is to survey some of the most successful model reduction methods in tutorial style articles and to present benchmark problems from several application areas for testing and comparing existing and new algorithms. As the discussed methods have often been developed in parallel in disconnected application areas, the intention of the mini-workshop in Oberwolfach and its proceedings is to make these ideas available to researchers and practitioners from all these different disciplines.
Author : Jiaxi Liang
Release : 2016
Genre : Algorithms
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Robustness in Dimensionality Reduction by : Jiaxi Liang
Download or read book Robustness in Dimensionality Reduction written by Jiaxi Liang. This book was released on 2016. Available in PDF, EPUB and Kindle. Book excerpt: Dimensionality reduction is widely used in many statistical applications, such as image analysis, microarray analysis, or text mining. This thesis focuses on three problems that relate to the robustness in dimension reduction. The first topic is the performance analysis in dimension reduction, that is, quantitatively assessing the performance of a algorithm on a given dataset. A criterion for success is established from the geometric point of view to address this issues. A family of goodness measures, called \textsl{local rank correlation}, is developed to assess the performance of dimensionality reduction methods. The potential application of the local rank correlation in selecting tuning parameters of dimension reduction algorithms is also explored. The second topic is the sensitivity analysis in dimension reduction. Two types of influence functions are developed as measures of robustness, based on which we develop graphical display strategies for visualizing the robustness of a dimension reduction method, and flagging potential outliers. In the third part of the thesis, a novel robust PCA framework, called \textsl{Performance-Weighted Bagging PCA}, is proposed from the perspective of model averaging. It obtains a robust linear subspace by weighted averaging a collection of subspaces produced by subsamples. The robustness against outliers is achieved by a proper weighting scheme, and possible choices of weighting scheme are investigated.
Author : Liang Sun
Release : 2013-11-04
Genre : Business & Economics
Kind : eBook
Book Rating : 152/5 ( reviews)
Book Synopsis Multi-Label Dimensionality Reduction by : Liang Sun
Download or read book Multi-Label Dimensionality Reduction written by Liang Sun. This book was released on 2013-11-04. Available in PDF, EPUB and Kindle. Book excerpt: Similar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality. An effective way to mitigate this problem is through dimensionality reduction, which extracts a small number of features by removing irrelevant, redundant, and noisy information. The data mining and machine learning literature currently lacks a unified treatment of multi-label dimensionality reduction that incorporates both algorithmic developments and applications. Addressing this shortfall, Multi-Label Dimensionality Reduction covers the methodological developments, theoretical properties, computational aspects, and applications of many multi-label dimensionality reduction algorithms. It explores numerous research questions, including: How to fully exploit label correlations for effective dimensionality reduction How to scale dimensionality reduction algorithms to large-scale problems How to effectively combine dimensionality reduction with classification How to derive sparse dimensionality reduction algorithms to enhance model interpretability How to perform multi-label dimensionality reduction effectively in practical applications The authors emphasize their extensive work on dimensionality reduction for multi-label learning. Using a case study of Drosophila gene expression pattern image annotation, they demonstrate how to apply multi-label dimensionality reduction algorithms to solve real-world problems. A supplementary website provides a MATLAB® package for implementing popular dimensionality reduction algorithms.
Author : Flavio Manenti
Release : 2024-06-27
Genre : Technology & Engineering
Kind : eBook
Book Rating : 259/5 ( reviews)
Book Synopsis 34th European Symposium on Computer Aided Process Engineering /15th International Symposium on Process Systems Engineering by : Flavio Manenti
Download or read book 34th European Symposium on Computer Aided Process Engineering /15th International Symposium on Process Systems Engineering written by Flavio Manenti. This book was released on 2024-06-27. Available in PDF, EPUB and Kindle. Book excerpt: The 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering, contains the papers presented at the 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering joint event. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. - Presents findings and discussions from the 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering joint event
