Probability and statistics

The importance of accurate recommender systems has been widely recognized by academia and industry, and recommendation is rapidly becoming one of the most successful applications of data mining and machine learning.

Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc.

Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade.

These days, nearly all the engineering problem are solved with the aid of suitable computer packages.

Feedback control systems is an important course in aerospace engineering, chemical engineering, electrical engineering, mechanical engineering, and mechatronics engineering, to name just a few.

This lecture provides an introduction to the field of mobile robotics and the intersection between multiple robotics-related disciplines including electrical, mechanical, computer, software engineering and computer science.

This book introduces the so-called "e;"e;stable factorization approach"e;"e; to the synthesis of feedback controllers for linear control systems.

This book discusses mixture and hidden Markov models for modeling behavioral data.

This monograph describes the Reaction Wheel Pendulum, the newest inverted-pendulum-like device for control education and research.

This book introduces the so-called "e;"e;stable factorization approach"e;"e; to the synthesis of feedback controllers for linear control systems.

Recent data shows that 87% of Artificial Intelligence/Big Data projects don't make it into production (VB Staff, 2019), meaning that most projects are never deployed.

This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability.

This book covers recent trends and applications of nonlinear dynamics in various branches of society, science, and engineering.

This textbook explores two distinct stochastic processes that evolve at random: weakly stationary processes and discrete parameter Markov processes.

This book is not a research monograph about Malliavin calculus with the latest results and the most sophisticated proofs.

This book discusses important applications of the Behrens-Fisher statistic and the False Discovery Rate (FDR).

This book offers a new theoretical framework within which to understand "e;the mind-body problem"e;.

This volume is a collection of research works to honor the late Professor Mark H.

This book provides a brief but accessible introduction to a set of related, mathematical ideas that have proved useful in understanding the brain and behaviour.

This volume presents the revised papers of the 14th International Conference in Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, MCQMC 2020, which took place online during August 10-14, 2020.

This volume draws upon one of the first comprehensive studies on the regional variations of services for aging persons in China to provide an empirical and theoretical understanding of the impact of China's rapidly growing aging population on the country's socioeconomic, cultural, and political systems.

This textbook presents the basics of probability and statistical estimation, with a view to applications.

The cooperation and contamination among mathematicians, statisticians and econometricians working in actuarial sciences and finance are improving the research on these topics and producing numerous meaningful scientific results.

More data has been produced in the 21st century than all of human history combined.

This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs).

This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context, based only on a limited dataset such as a random sample drawn from a larger population.

Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis.

This book establishes a unified framework for dealing with typical engineering complications arising in modern, complex, large-scale networks such as parameter uncertainties, missing measurement and cyber-attack.

This short book elaborates on selected aspects of stochastic-statistical dependencies in multivariate statistics.

Focusing on comprehensive comparisons of the performance of stochastic optimization algorithms, this book provides an overview of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked.

This volume presents a selection of texts that reflects the current research streams in probability, with an interest toward topics such as filtrations, Markov processes and Markov chains as well as  large deviations, Stochastic Partial Differential equations, rough paths theory, quantum probabilities and percolation on graphs.

The computational models of physical systems comprise parameters, independent and dependent variables.

This book introduces the reader to Six Sigma, a problem-solving technique for reducing defects and variation in processes.

This book discusses diverse concepts and notions - and their applications - concerning probability and random variables at the intermediate to advanced level.

The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures.

This second volume of Research in Computational Topology is a celebration and promotion of research by women in applied and computational topology, containing the proceedings of the second workshop for Women in Computational Topology (WinCompTop) as well as papers solicited from the broader WinCompTop community.

This book explores the methodological strategies for linking philosophy and neuroscience concerning the study of the conscious brain.

This book provides a comprehensive guide on how geographic information systems (GIS) can be used to optimize solar energy resources.

This book constitutes the Second Diabetic Foot Ulcers Grand Challenge, DFUC 2021, which was held on September 27, 2021, in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021.

This book provides numerous examples of linear and nonlinear model applications.

This book provides a complete introduction into spatial networks.

This book provides a comprehensive methodology to measure systemic risk in many of its facets and dimensions based on state-of-the-art risk assessment methods.

This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners.

This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning.

This textbook provides clear and accessible guidance on the importance and practical application of mixed-methods research.

This book is the second volume of a two-volume monograph devoted to the study of limit and ergodic theorems for regularly and singularly perturbed Markov chains, semi-Markov processes, and multi-alternating regenerative processes with semi-Markov modulation.

This book explores Complex System Governance (CSG)-an emerging field concerned with the design, execution, and evolution of essential functions necessary to ensure continued viability of a system.

This state-of-the-art book brings together the full range of issues that can inform care for patients experiencing the effects of concussion.

This textbook, now in its third edition, offers a practical introduction to probability with statistical applications, covering material for both a first and second undergraduate probability course.

This book provides a friendly introduction to the paradigm and proposes a broad panorama of killing applications of the Infinity Computer in optimization: radically new numerical algorithms, great theoretical insights, efficient software implementations, and interesting practical case studies.