Ning Cai was an eminent mathematician, engineer and computer scientist who made many significant contributions to information theory. In particular, his work on network coding theory created a new research direction for the community.Prof. Cai’s passion for science inspired his collaborators across the fields of classical and quantum information theory, combinatorics, computation, post-Shannon theory, and coding theory, and the contributions in this volume reflect his success as a ...

In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on kernel-based approximation methods and demonstrates their implementation in various settings. The authors explore the historical context of this fascinating topic and explain recent advances as strategies to address long-standing problems. Examples are drawn from fields as diverse as function ...

Analysis, assessment, and data management are core competencies for operation research analysts. This volume addresses a number of issues and developed methods for improving those skills. It is an outgrowth of a conference held in April 2013 at the Hellenic Military Academy, and brings together a broad variety of mathematical methods and theories with several applications. It discusses directions and pursuits of scientists that pertain to engineering sciences. It is also presents the theor...

Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques.Divided in...

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature re...

This open access book constitutes the proceedings of the 36th International Conference on Computer-Aided Verification, CAV 2024, which took place in Montreal, Canada, during July 24–27, 2024.The primary focus of CAV is to extend the frontiers of verification techniques by expanding to new domains such as security, quantum computing, and machine learning.

This book constitutes the refereed proceedings of the 26th International Workshop on Computer Algebra in Scientific Computing, CASC 2024, which took place in Rennes, France, during September 2 - September 6, 2024.The 19 full papers included in this book were carefully reviewed and selected from 23 submissions. The annual International Workshop CASC 2024 aims to bring together researchers in theoretical computer algebra (CA), engineers, scholars, as well as other allied professional...

This seven-volume set, LNCS 16541-16547, constitutes the proceedings of the 45th Annual International Conference on the Theory and Applications of Cryptographic Techniques, EUROCRYPT 2026, held in Rome, Italy, during May 10–14, 2026.The 142 papers included in these proceedings were carefully reviewed and selected from 675 submissions. They are organized in topical sections as follows:Part I: Signatures; Quantum CryptographyPart II: Applied CryptographyPart III:...

“The book is outstanding and admirable in many respects. ... is necessary reading for all kinds of readers from undergraduate students to top authorities in the field.” Journal of Symbolic LogicWritten by two experts in the field, this is the only comprehensive and unified treatment of the central ideas and applications of Kolmogorov complexity. The book presents a thorough treatment of the subject with a wide range of illustrative applications. Such applications include the random...

This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and un...

Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. It provides insight into the ideas behind the models and their algorithms, giving details of their formulation and deduction. The main applications included are video denoising, background modeling, image alignment and rectification, motion segmentation, image segmentation and image saliency detection. Readers will learn which...

Presenting the latest findings in the field of numerical analysis and optimization, this volume balances pure research with practical applications of the subject. Accompanied by detailed tables, figures, and examinations of useful software tools, this volume will equip the reader to perform detailed and layered analysis of complex datasets.Many real-world complex problems can be formulated as optimization tasks. Such problems can be characterized as large scale, unconstrained, cons...