Algorithmic Advances in Riemannian Geometry and Applications
Title | Algorithmic Advances in Riemannian Geometry and Applications PDF eBook |
Author | Hà Quang Minh |
Publisher | Springer |
Pages | 216 |
Release | 2016-10-05 |
Genre | Computers |
ISBN | 3319450263 |
This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using the mathematical machinery of Riemannian geometry. As demonstrated by all the chapters in the book, when the data is intrinsically non-Euclidean, the utilization of this geometrical information can lead to better algorithms that can capture more accurately the structures inherent in the data, leading ultimately to better empirical performance. This book is not intended to be an encyclopedic compilation of the applications of Riemannian geometry. Instead, it focuses on several important research directions that are currently actively pursued by researchers in the field. These include statistical modeling and analysis on manifolds,optimization on manifolds, Riemannian manifolds and kernel methods, and dictionary learning and sparse coding on manifolds. Examples of applications include novel algorithms for Monte Carlo sampling and Gaussian Mixture Model fitting, 3D brain image analysis,image classification, action recognition, and motion tracking.
Riemannian Computing in Computer Vision
Title | Riemannian Computing in Computer Vision PDF eBook |
Author | Pavan K. Turaga |
Publisher | Springer |
Pages | 382 |
Release | 2015-11-09 |
Genre | Technology & Engineering |
ISBN | 3319229575 |
This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours).
System- and Data-Driven Methods and Algorithms
Title | System- and Data-Driven Methods and Algorithms PDF eBook |
Author | Peter Benner |
Publisher | Walter de Gruyter GmbH & Co KG |
Pages | 346 |
Release | 2021-11-08 |
Genre | Mathematics |
ISBN | 3110497719 |
An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.
Riemannian Optimization and Its Applications
Title | Riemannian Optimization and Its Applications PDF eBook |
Author | Hiroyuki Sato |
Publisher | Springer Nature |
Pages | 129 |
Release | 2021-02-17 |
Genre | Technology & Engineering |
ISBN | 3030623912 |
This brief describes the basics of Riemannian optimization—optimization on Riemannian manifolds—introduces algorithms for Riemannian optimization problems, discusses the theoretical properties of these algorithms, and suggests possible applications of Riemannian optimization to problems in other fields. To provide the reader with a smooth introduction to Riemannian optimization, brief reviews of mathematical optimization in Euclidean spaces and Riemannian geometry are included. Riemannian optimization is then introduced by merging these concepts. In particular, the Euclidean and Riemannian conjugate gradient methods are discussed in detail. A brief review of recent developments in Riemannian optimization is also provided. Riemannian optimization methods are applicable to many problems in various fields. This brief discusses some important applications including the eigenvalue and singular value decompositions in numerical linear algebra, optimal model reduction in control engineering, and canonical correlation analysis in statistics.
CONTROLO 2020
Title | CONTROLO 2020 PDF eBook |
Author | José Alexandre Gonçalves |
Publisher | Springer Nature |
Pages | 810 |
Release | 2020-09-08 |
Genre | Technology & Engineering |
ISBN | 3030586537 |
This book offers a timely and comprehensive snapshot of research and developments in the field of control engineering. Covering a wide range of theoretical and practical issues, the contributions describes a number of different control approaches, such adaptive control, fuzzy and neuro-fuzzy control, remote and robust control systems, real time an fault tolerant control, among others. Sensors and actuators, measurement systems, renewable energy systems, aerospace systems as well as industrial control and automation, are also comprehensively covered. Based on the proceedings of the 14th APCA International Conference on Automatic Control and Soft Computing, held on July 1-3, 2020, in Bragança, Portugal, the book offers a timely and thoroughly survey of the latest research in the field of control, and a source of inspiration for researchers and professionals worldwide.
CONTROLO 2022
Title | CONTROLO 2022 PDF eBook |
Author | Luís Brito Palma |
Publisher | Springer Nature |
Pages | 750 |
Release | 2022-07-02 |
Genre | Technology & Engineering |
ISBN | 3031100476 |
This book offers a timely and comprehensive snapshot of research and developments in the fields of dynamic systems and control engineering. Covering a wide range of theoretical and practical issues, the contributions describes a number of different control approaches, such as PID control, adaptive control, nonlinear systems and control, intelligent monitoring and control based on fuzzy and neural systems, robust control systems, and real time control, among others. Sensors and actuators, measurement systems, renewable energy systems, aeronautic and aerospace systems as well as industrial control and automation, are also comprehensively covered. Based on the proceedings of the 15th APCA International Conference on Automatic Control and Soft Computing, held on July 6-8, 2022, in Caparica, Portugal, the book offers a timely and thoroughly survey of the latest research in the fields of dynamic systems and automatic control engineering, and a source of inspiration for researchers and professionals worldwide.
Machine Learning and Knowledge Discovery in Databases
Title | Machine Learning and Knowledge Discovery in Databases PDF eBook |
Author | Michele Berlingerio |
Publisher | Springer |
Pages | 866 |
Release | 2019-01-22 |
Genre | Computers |
ISBN | 3030109283 |
The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.