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Fuzzy Systems and Data Mining IV
Big Data Analytics is on the rise in the last years of the current decade. Data are overwhelming the computation capacity of high performance servers. Cloud, grid, edge and fog computing are a few examples of the current hype. Computational Intelligence offers two faces to deal with the development of models: on the one hand, the crisp approach, which considers for every variable an exact value and, on the other hand, the fuzzy focus, which copes with values between two boundaries. This book presents 114 papers from the 4th International Conference on Fuzzy Systems and Data Mining (FSDM 2018), held in Bangkok, Thailand, from 16 to 19 November 2018. All papers were carefully reviewed by program committee members, who took into consideration the breadth and depth of the research topics that fall within the scope of FSDM. The acceptance rate was 32.85% . Offering a state-of-the-art overview of fuzzy systems and data mining, the publication will be of interest to all those whose work involves data science.
Computer Vision – ECCV 2018
The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.
Machine Learning and Knowledge Discovery in Databases
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge grap...
Data Science
This two volume set (CCIS 727 and 728) constitutes the refereed proceedings of the Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017 (originally ICYCSEE) held in Changsha, China, in September 2017. The 112 revised full papers presented in these two volumes were carefully reviewed and selected from 987 submissions. The papers cover a wide range of topics related to Basic Theory and Techniques for Data Science including Mathematical Issues in Data Science, Computational Theory for Data Science, Big Data Management and Applications, Data Quality and Data Preparation, Evaluation and Measurement in Data Science, Data Visualization, Big Data Mi...
Urban Construction and Management Engineering IV
Urban Construction and Management Engineering IV focuses on the research of construction technology and the engineering management in urban construction. This proceedings gathers the most cutting-edge research and achievements, and will provide scholars and engineers with preferable research directions and engineering solutions as reference. Subjects in this proceedings include: Civil Engineering Engineering Structure Engineering Management Low Carbon City Urban Management The works of this proceedings encourages development of civil engineering and construction technology. Thereby, the work promotes scientific information interchange between scholars from the top universities, research centers and high-tech enterprises working all around the world.
Cloud Computing and Big Data
This book constitutes the refereed proceedings of the Second International Conference on Cloud Computing and Big Data, CloudCom-Asia 2015, held in Huangshan, China, in June 2015. The 29 full papers and two keynote speeches were carefully reviewed and selected from 106 submissions. The papers are organized in topical sections on cloud architecture; applications; big data and social network; security and privacy.
Predictive Intelligence in Medicine
This book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.* The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine. *The workshop was held virtually.
Mobile Ad-hoc and Sensor Networks
This book constitutes the refereed proceedings of the First International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2005, held in Wuhan, China in December 2005. The volume also contains 12 papers of the MSN workshop on Modeling and the Security in the Next Generation Mobile Information Systems (MSNG 2005). The 112 revised full papers were carefully reviewed and selected from a total of 512 submissions. The papers address all current topical areas in mobile ad hoc and sensor networks such as network architecture and protocols, software platforms and development tools, self-organization and synchronization, routing and data dissemination, failure resilience and fault isolation, energy management, data, information, and signal processing, security and privacy, network planning, provisioning, and deployment, network modeling and performance evaluation, developments and applications, as well as integration with other systems.
Mathematical Aspects of Deep Learning
In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.
