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This book provides a structured introduction to automata theory, bridging theoretical foundations with... Læs mere
This book provides a practical guide to solving problems with quantum algorithms and hands-on... Læs mere
The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores... Læs mere
Explores the cutting-edge integration of generative AI techniques to enhance environmental remote sensing, providing a... Læs mere
The book integrates concepts from various disciplines, including quantum mechanics, algebra, and information theory, providing a comprehensive understanding of how these fields intersect and contribute to advances in coding theory and cryptography.
Diversity-Driven Evolutionary Algorithms For Solving Engineering Problems explores optimization algorithms and their applications across diverse engineering domains.
Bias and Beyond is anchored in a commitment to Diversity, Equity, and Inclusion (DEI), not only as aspirational values but as methodological imperatives that must inform every aspect of data practice.
An accessible introductory to advanced text focusing on integrating scientific computing methods and algorithms with modern data analysis techniques, including basic applications of machine learning in the sciences and engineering.
This Element introduces computability theory and its use in explaining empirical phenomena. Aimed at advanced undergraduates and graduates in philosophy, it... Læs mere
This book presents a semantic-based explainable framework based on knowledge graph and semantic web technology focusing on designing XAI system that... Læs mere
This textbook for upper-year undergraduates and graduates concentrates on mining networks, a subfield within data science. Changes and updates to this edition include: new... Læs mere