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The Proceedings of ICUEMS 2022 will be useful to professionals, academics, and Ph.D. students interested in the above-mentioned fields. Emphasis was put on basic methodologies, scientific development and engineering applications.
Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques.In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems for the end-to-end data science or ML lifecycle. We review multiple interconnected lines of work: (1) ML support in database (DB) systems, (2) DB-inspired ML systems, and (3) ML lifecycle systems. Covered topics include: in-database analytics via query generation and user-defined functions, factorized and statistical-relational learning; optimizing compilers for ML workloads; execution strategies and hardware accelerators; data access methods such as compression, partitioning and indexing; resource elasticity and cloud markets; as well as systems for data preparation for ML, model selection, model management, model debugging, and model serving. Given the rapidly evolving field, we strive for a balance between an up-to-date survey of ML systems, an overview of the underlying concepts and techniques, as well as pointers to open research questions. Hence, this book might serve as a starting point for both systems researchers and developers.
are essential to the quality of the program. We are grateful to Weiyi Meng, X. Sean Wang, Stratis D. Viglas, and Je?rey Xu Yu for their valuable help in leading and monitoring the discussions on our behalf. We also thank Jun Yang for his work in preparing the proceedings. Finally, we are deeply indebted to Yu Zhang and Mengya Tang, the Web Masters, who took on tremendous pain and extra work, and ably modi?ed, extended and maintained the conference management tool; for three long months they worked until late night every day, seven days a week; the necessary extension of the tool also received help from Kun Jing, Chengchao Xie, Shiqi Peng, Heng Wang, Cheng Jin and Ruizhi Ye; without their hardande?ectiveworkthe onlinediscussionswouldnothavebeen possible, among other things. October 2005 Wenfei Fan, Zhaohui Wu Program Committee Co-chairs WAIM 2005 Dedication: Hongjun Lu (1945-2005) On behalf of the Program Committee, it is with sincere gratitude and great sorrow that we would like to dedicate WAIM 2005 proceedings to Hongjun Lu, who left us on March 3, 2005. Hongjun was not only an excellent researcher and highly productive scholar of the database community, but also a wond- ful colleague and dear friend. For many years, he has been the ambassador for database research to China, and tremendously fostered the growth of this community.
This book introduces the reliability modelling and optimization of warm standby systems. Warm standby is an attractive redundancy technique, as it consumes less energy than hot standby and switches into the active state faster than cold standby.
Volumes 1-3 of the 6 volume monograph on Jun Yang - the architecture echoing the name changes over the years.
The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control.
This book introduces the latest research developments in composite nanomaterials and summarizes the fundamentals and technical approaches in synthesis, fabrication and processing of composite nanomaterials.
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