Jieping ye (4 Ergebnisse)

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.…

Gebunden. Zustand: New. Liang Sun is a scientist in the R&ampD of Opera Solutions, a leading company in big data science and predictive analytics. He received a PhD in computer science from Arizona State University. His research interests lie broadly in the ar.

Buch. Zustand: Neu. Neuware - A comprehensive reference for researchers in machine learning, data mining, and computer vision, this book presents in-depth, systematic discussions on algorithms and applications for dimensionality reduction. It covers emerging models for general dimensionality reduction in multi-label classification. The book also presents a novel framework to unify a variety of models. Based on the discussions of the models and theory, the authors provide thorough analysis and comparison of the algorithms used in these models. They also include applications of these models and algorithms in bioinformatics and biomedical informatics. A supporting website provides updated information.…