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  • © 2016

Solving Large Scale Learning Tasks. Challenges and Algorithms

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

  • 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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Table of contents (21 chapters)

  1. Front Matter

    Pages I-XIV
  2. Online Social Networks Event Detection: A Survey

    • Mário Cordeiro, João Gama
    Pages 1-41
  3. Detecting Events in Online Social Networks: Definitions, Trends and Challenges

    • Nikolaos Panagiotou, Ioannis Katakis, Dimitrios Gunopulos
    Pages 42-84
  4. Why Do We Need Data Privacy?

    • Volker Klingspor
    Pages 85-95
  5. Sharing Data with Guaranteed Privacy

    • Arno Siebes
    Pages 96-108
  6. Distributed Support Vector Machines: An Overview

    • Marco Stolpe, Kanishka Bhaduri, Kamalika Das
    Pages 109-138
  7. Knowledge Discovery from Complex High Dimensional Data

    • Sangkyun Lee, Andreas Holzinger
    Pages 148-167
  8. Local Pattern Detection in Attributed Graphs

    • Jean-François Boulicaut, Marc Plantevit, Céline Robardet
    Pages 168-183
  9. Understanding Human Mobility with Big Data

    • Fosca Giannotti, Lorenzo Gabrielli, Dino Pedreschi, Salvatore Rinzivillo
    Pages 208-220
  10. Compressible Reparametrization of Time-Variant Linear Dynamical Systems

    • Nico Piatkowski, François Schnitzler
    Pages 234-250
  11. Collaborative Online Learning of an Action Model

    • Christophe Rodrigues, Henry Soldano, Gauvain Bourgne, Céline Rouveirol
    Pages 300-319
  12. Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction

    • Sriraam Natarajan, Ameet Soni, Anurag Wazalwar, Dileep Viswanathan, Kristian Kersting
    Pages 331-345

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.

Editors and Affiliations

  • TU Dortmund , Dortmund, Germany

    Stefan Michaelis, Nico Piatkowski

  • TU Dortmund , Dortmund, Germany

    Marco Stolpe

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access