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Solving Large Scale Learning Tasks. Challenges and Algorithms

Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday

  • Book
  • © 2016

Overview

  • 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

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9580)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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About this book

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.

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Keywords

Table of contents (21 chapters)

Editors and Affiliations

  • TU Dortmund , Dortmund, Germany

    Stefan Michaelis, Nico Piatkowski

  • TU Dortmund , Dortmund, Germany

    Marco Stolpe

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