Kategoria BISAC: Computers >> Information Theory

This book constitutes the refereed proceedings of the Cryptographer's Track at the RSA Conference 2022, CT-RSA 2022, held in San Francisco, CA, USA, in February 2022.*

The 24 full papers presented in this volume were carefully reviewed and selected from 87 submissions.

CT-RSA is the track devoted to scientific papers on cryptography, public-key to symmetric-key cryptography and from crypto-graphic protocols to primitives and their implementation security.

*The conference was held as a hybrid event.

The 40 papers included in these proceedings were carefully reviewed and selected from 137 submissions. They focus on all aspects of public-key cryptography, covering cryptanalysis; MPC and secret sharing; cryptographic...

This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems.

In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine...

This open access book constitutes the proceedings of the 25th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2022, which was held during April 4-6, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022.

The 23 regular papers presented in this volume were carefully reviewed and selected from 77 submissions. They deal with research on theories and methods to support the analysis, integration, synthesis, transformation, and verification of programs and software...

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than relying on knowledge or experience. This textbook addresses the fundamentals of kernel methods for machine learning by considering relevant math problems and building R programs. 

The book’s main features are as follows:

• The content is written in an easy-to-follow and self-contained style.
• The book includes 100 exercises, which have been carefully selected and refined. As their solutions are provided in the main text, readers can...