Solving Large Scale Learning Tasks. Challenges and Algorithms
Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday
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Beschreibung
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.
Contains refereed papers dedicated to Katharina Morik and to her work Collects a number of papers by Prof. Morik's friends and collaborators over the years presenting a broad range of topics reflecting her versatility Adresses a large diversity of topics starting with natural language processing; machine learning, ranging from inductive logic programming to statistical learning; analysis of very large data collections; high-dimensional data; and resource awareness. Latest results include spatio-temporal random fields and integer Markov random fields, both allowing for complex probabilistic graphical models under resource constraints. Includes supplementary material: sn.pub/extras
Autor*in
Stefan Michaelis
Themen in »Solving Large Scale Learning Tasks. Challenges and Algorithms«
big data analytics distributed data mining high-performance computing social network analysis spatio-temporal analysis attributed graph mining classification evaluation event detection markov process mining social media mobility data mining ontology single and multiagent learning social media