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Quantifying and Processing Biomedical and Behavioral Signals
The book is based on interdisciplinary research on various aspects and dynamics of human multimodal signal exchanges. It discusses realistic application scenarios where human interaction is the focus, in order to identify new methods for data processing and data flow coordination through synchronization, and optimization of new encoding features combining contextually enacted communicative signals, and develop shared digital data repositories and annotation standards for benchmarking the algorithmic feasibility and successive implementation of believable human–computer interaction (HCI) systems. This book is a valuable resource for a. the research community, PhD students, early stage researchers c. schools, hospitals, and rehabilitation and assisted-living centers e. the ICT market, and representatives from multimedia industries
Logics in Artificial Intelligence
This book constitutes the proceedings of the 16th European Conference on Logics in Artificial Intelligence, JELIA 2019, held in Rende, Italy, in May 2019. The 50 full papers and 10 short papers included in this volume were carefully reviewed and selected from 101 submissions. Additionally, the book contains 3 invited papers. The accepted papers span a number of areas within Logics in AI, including: belief revision and argumentation; causal, defeasible and inductive reasoning; conditional, probabilistic and propositional logic; description logics; logic programming; modal and default logic; and temporal logic.
Intelligent Computing
This book presents the proceedings of the Computing Conference 2019, providing a comprehensive collection of chapters focusing on core areas of computing and their real-world applications. Computing is an extremely broad discipline, encompassing a range of specialized fields, each focusing on particular areas of technology and types of application, and the conference offered pioneering researchers, scientists, industrial engineers, and students from around the globe a platform to share new ideas and development experiences. Providing state-of-the-art intelligent methods and techniques for solving real- world problems, the book inspires further research and technological advances in this important area.
Rules and Reasoning
This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2018, held in Luxembourg during September 2018. This is the second conference of a new series, joining the efforts of two existing conference series, namely “RuleML” (International Web Rule Symposium) and “RR” (Web Reasoning and Rule Systems). The 10 full research papers presented together with 5 long technical communications and 7 short papers were carefully reviewed and selected from 33 submissions.
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Data Science Concepts and Techniques with Applications
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared ...
Graph Data Processing with Cypher
Get acquainted with Cypher in a guided manner quickly and learn how to query the graph databases with efficient and performant queries Key Features Work with Cypher syntax and semantics while building graph traversal queries Get up and running with advanced Cypher concepts like List, Maps, OPTIONAL MATCH Master best practices in writing effective queries leveraging data modeling and patterns Book DescriptionWhile it is easy to learn and understand the Cypher declarative language for querying graph databases, it can be very difficult to master it. As graph databases are becoming more mainstream, there is a dearth of content and guidance for developers to leverage database capabilities fully. ...
Machine Learning for Imbalanced Data
Take your machine learning expertise to the next level with this essential guide, utilizing libraries like imbalanced-learn, PyTorch, scikit-learn, pandas, and NumPy to maximize model performance and tackle imbalanced data Key Features Understand how to use modern machine learning frameworks with detailed explanations, illustrations, and code samples Learn cutting-edge deep learning techniques to overcome data imbalance Explore different methods for dealing with skewed data in ML and DL applications Purchase of the print or Kindle book includes a free eBook in the PDF format Book DescriptionAs machine learning practitioners, we often encounter imbalanced datasets in which one class has consi...
Modern Graph Theory Algorithms with Python
Solve challenging and computationally intensive analytics problems by leveraging network science and graph algorithms Key Features Learn how to wrangle different types of datasets and analytics problems into networks Leverage graph theoretic algorithms to analyze data efficiently Apply the skills you gain to solve a variety of problems through case studies in Python Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWe are living in the age of big data, and scalable solutions are a necessity. Network science leverages the power of graph theory and flexible data structures to analyze big data at scale. This book guides you through the basics of network science, sho...
