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This volume features a collection of papers and lecture notes from the “XIV Symposium on Probability and Stochastic Processes,” held at the Center for Research in Mathematics (CIMAT), Mexico, in November 2023. Contributions discuss state-of-the-art...
This open access book is a comprehensive guide that delves into the statistical methodologies used in public health and infectious disease surveillance. It contrasts the foundational principles and methodologies of both Bayesian and Frequentist statistical approaches,...
This book proposes a new mathematical methodology for addressing first passage problems, particularly in various classical stochastic models of applied probability.This approach is based on the so-called Abel-Gontcharoff (A-G) pseudopolynomials and the associated A-G...
This volume comprises selected peer-reviewed proceedings of the 12th International Conference on Signal Processing and Integrated Networks (SPIN 2025). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in signal...
Ergodic theorems are a cornerstone of the theory of stochastic processes and their applications. This book is the second volume of a two-volume monograph dedicated to ergodic theorems. While the first volume centers on Markovian and...
Ergodic theorems are a cornerstone of the theory of stochastic processes and their applications. This volume delves into ergodic theorems with explicit power and exponential upper bounds for convergence rates, focusing on Markov chains, renewal processes, and...
Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented—balancing rigorous quantum theory with...
This book presents the select proceedings of the 4th Biennial International Conference on Future Learning Aspects for Mechanical Engineering (FLAME 2024). It covers the applications of machine learning (ML) and artificial intelligence (AI) in the development of smart...
This volume explores the forefront of AI innovation in building secure, sustainable, and intelligent systems. From adaptive blockchain solutions for IoT and advances in photonic quantum computing to DNS-based cyber defense and disaster-resilient sensor networks, the...
Concise and approachable yet rigorous discussion of the appropriate use of statistical techniques in life science research Basic Statistics for Life Scientists is an approachable, concise handbook of essential statistical techniques that teaches correct practice in the...
This volume showcases transformative AI research addressing real-world challenges across healthcare, education, law, and digital security. Highlights include explainable deep learning for berry classification, AI-driven communication skill assessment in virtual...
This book presents recent findings on central and non-central limit theorems for Toeplitz and tapered Toeplitz random quadratic functionals of stationary processes, with applications in spectral-based statistical inference. It focuses on Gaussian, orthogonal...
The original contributions on Bayesian econometrics gathered in this book pay tribute to Sune Karlsson, celebrating his significant work in time series econometrics and its applications in macroeconomics and finance.The volume consists of both methodological and...
This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs), along with numerical methods for computing parabolic partial differential equations (PDEs)....
Für viele NP-schwere Losgrößenprobleme stehen diverse Heuristiken zur Verfügung, die je nach Eigenschaft der Instanz unterschiedliche Lösungsqualitäten und Rechenzeiten aufweisen. Mit zunehmender Problemgröße steigen die...
This book provides an overview of some classical linear methods in Multivariate Data Analysis.This is an old domain, well established since the 1960s, and refreshed timely as a key step in statistical learning. It can be presented as part of statistical learning, or as...
Probability and statistics are subjects fundamental to data analysis, making them essential for efficient artificial intelligence. Although the foundational concepts of probability and statistics remain constant, what needs to be taught is constantly evolving. The...
This book provides a data-driven analysis of shared micromobility in China. Both bike-sharing and e-bike-sharing are considered and several Chinese cities (e.g., Shanghai and Hangzhou) are selected as study cases. It adopts a variety of methods including GIS, big data...
Next-Generation Computational Intelligence: Trends and Technologies explores the transformative potential of advanced computational intelligence (CI) methods and their application across modern industries. With the rapid evolution of artificial intelligence, machine...
This book is about copies-based nonparametric estimation of the drift function in stochastic differential equations (SDEs) driven by Brownian motion, a jump process, or fractional Brownian motion. While the estimators of the drift function in SDEs are classically...
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