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Andreas Rauber

Andreas Rauber

D-Index & Metrics

Computer Science

D-Index
47
Citations
9000
World Ranking
6487
National Ranking
50

Overview

Andreas Rauber is affiliated with TU Wien in Austria and has contributed extensively to the field of Computer Science, with a total of 103 publications focused on various subfields.

The main subfields in which they have published include:

  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Management Science and Operations Research

Their research covers a broad range of topics, with a concentration in:

  • Scientific Computing and Data Management
  • Research Data Management Practices
  • Privacy-Preserving Technologies in Data
  • Network Security and Intrusion Detection
  • Anomaly Detection Techniques and Applications
  • Adversarial Robustness in Machine Learning
  • Software System Performance and Reliability

Frequent co-authors collaborating with Andreas Rauber include:

  • Max Landauer
  • Florian Skopik
  • Markus Wurzenberger
  • Katharina Flicker
  • Rudolf Mayer

The venues where Andreas Rauber has most commonly published are:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • International Journal of Digital Curation
  • ACM Transactions on Management Information Systems
  • Data Science Journal

Recent papers by Andreas Rauber demonstrate a focus on cybersecurity, machine learning, and data analysis, including:

  • System log clustering approaches for cyber security applications: A survey, 2020, Computers & Security
  • I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences, 2023, ACM Computing Surveys
  • Have it Your Way: Generating Customized Log Datasets With a Model-Driven Simulation Testbed, 2020, IEEE Transactions on Reliability
  • Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation, 2022, ACM Transactions on Privacy and Security
  • Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks, 2023, IEEE Transactions on Neural Networks and Learning Systems

Best Publications

  • The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data

    A. Rauber;D. Merkl;M. Dittenbach

  • Content-based organization and visualization of music archives

    Elias Pampalk;Andreas Rauber;Dieter Merkl

  • The growing hierarchical self-organizing map

    M. Dittenbach;D. Merkl;A. Rauber

  • Using smoothed data histograms for cluster visualization in Self-Organizing Maps

    Elias Pampalk;Andreas Rauber;Dieter Merkl

  • EVALUATION OF FEATURE EXTRACTORS AND PSYCHO-ACOUSTIC TRANSFORMATIONS FOR MUSIC GENRE CLASSIFICATION

    Thomas Lidy;Andreas Rauber

  • Uncovering hierarchical structure in data using the growing hierarchical self-organizing map

    Michael Dittenbach;Andreas Rauber;Dieter Merkl

  • Systematic planning for digital preservation: evaluating potential strategies and building preservation plans

    Christoph Becker;Hannes Kulovits;Mark Guttenbrunner;Stephan Strodl

  • LifeCLEF 2015: Multimedia Life Species Identification Challenges

    Alexis Joly;Hervé Goëau;Hervé Glotin;Concetto Spampinato

  • Using Psycho-Acoustic Models and Self-Organizing Maps to Create a Hierarchical Structuring of Music by Musical Styles.

    Andreas Rauber;Elias Pampalk;Dieter Merkl

  • How to choose a digital preservation strategy: evaluating a preservation planning procedure

    Stephan Strodl;Christoph Becker;Robert Neumayer;Andreas Rauber

  • RHYME AND STYLE FEATURES FOR MUSICAL GENRE CLASSIFICATION BY SONG LYRICS

    Rudolf Mayer;Robert Neumayer;Andreas Rauber

  • The SOM-enhanced JukeBox: Organization and Visualization of Music Collections Based on Perceptual Models

    A. Rauber

  • Achieving human and machine accessibility of cited data in scholarly publications

    Joan Starr;Eleni Castro;Mercè Crosas;Michel Dumontier

  • Visual Methods for Analyzing Probabilistic Classification Data

    Bilal Alsallakh;Allan Hanbury;Helwig Hauser;Silvia Miksch

  • LabelSOM: on the labeling of self-organizing maps

    A. Rauber

  • Integrating automatic genre analysis into digital libraries

    Andreas Rauber;Alexander Müller-Kögler

  • Automatically Analyzing and Organizing Music Archives

    Andreas Rauber;Markus Frühwirth

  • PlaySOM and PocketSOMPlayer, Alternative Interfaces to Large Music Collections

    Robert Neumayer;Michael Dittenbach;Andreas Rauber

  • Improving Genre Classification by Combination of Audio and Symbolic Descriptors Using a Transcription Systems.

    Thomas Lidy;Andreas Rauber;Antonio Pertusa;José Manuel Iñesta Quereda

  • Keeping the Game Alive: Evaluating Strategies for the Preservation of Console Video Games

    Mark Guttenbrunner;Christoph Becker;Andreas Rauber

Frequent Co-Authors

Alexis Joly
Alexis Joly French Institute for Research in Computer Science and Automation - INRIA
Henning Müller
Henning Müller University of Applied Sciences and Arts Western Switzerland
Concetto Spampinato
Concetto Spampinato University of Catania
Jun Liu
Jun Liu Infinia ML (United States)
Joemon M. Jose
Joemon M. Jose University of Glasgow
Jane Hunter
Jane Hunter University of Technology Sydney
Fabrizio Sebastiani
Fabrizio Sebastiani Institute of Information Science and Technologies
Norbert Fuhr
Norbert Fuhr University of Duisburg-Essen

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