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Book
Solving Large Scale Learning Tasks. Challenges and Algorithms : Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday
Authors: --- ---
ISBN: 3319417053 3319417061 Year: 2016 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

In celebration of Prof. Morik's 60th birthday, this Festschrift covers research areas that Prof. Morik worked in and presents various researchers with whom she collaborated. The 23 refereed articles in this Festschrift volume provide challenges and solutions from theoreticians and practitioners on data preprocessing, modeling, learning, and evaluation. Topics include data-mining and machine-learning algorithms, feature selection and feature generation, optimization as well as efficiency of energy and communication.

Keywords

Computer science. --- Computer communication systems. --- Algorithms. --- Database management. --- Data mining. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Information Systems Applications (incl. Internet). --- Computer Communication Networks. --- Algorithm Analysis and Problem Complexity. --- Data Mining and Knowledge Discovery. --- Database Management. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Algorism --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Informatics --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Database searching --- Algebra --- Arithmetic --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Science --- Foundations --- Distributed processing --- Computer software. --- Artificial Intelligence. --- Software, Computer --- Computer systems --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software


Book
Machine Learning under Resource Constraints.
Authors: --- --- --- --- --- et al.
ISBN: 3110785986 3110785978 Year: 2022 Publisher: Berlin ; Boston : De Gruyter,

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Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 3 describes how the resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples. In the areas of health and medicine, it is demonstrated how machine learning can improve risk modelling, diagnosis, and treatment selection for diseases. Machine learning supported quality control during the manufacturing process in a factory allows to reduce material and energy cost and save testing times is shown by the diverse real-time applications in electronics and steel production as well as milling. Additional application examples show, how machine-learning can make traffic, logistics and smart cities more effi cient and sustainable. Finally, mobile communications can benefi t substantially from machine learning, for example by uncovering hidden characteristics of the wireless channel.

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