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Dr. Christiane Lammersen

Christiane

Zur Zeit: Softwareentwicklerin bei der SAP SE

Forschungsinteressen: Entwicklung und Analyse von Algorithmen und Datenstrukturen
zur Verarbeitung von riesigen Datenmengen
Forschungsthemen beinhalten: (randomisierte) Datenstromalgorithmen, Clusteringalgorithmen,
maschinelles Lernen, algorithmische und kombinatorische Geometrie, Graphentheorie

Veröffentlichungen

Journalartikel

  • Christiane Lammersen, Melanie Schmidt, and Christian Sohler (2015):
    Probabilistic k-Median Clustering in Data Streams.
    Theory of Computing Systems, 56(1): 251-290, 2015.
  • Joachim Gehweiler, Christiane Lammersen, and Christian Sohler (2014):
    A distributed O(1)-approximation algorithm for the uniform facility location problem.
    Algorithmica, 68(3): 643-670, 2014.
  • Marcel R. Ackermann, Christiane Lammersen, Marcus Märtens, Christoph Raupach, Christian Sohler, and Kamil Swierkot (2012):
    StreamKM++: A clustering algorithm for data streams.
    ACM Journal of Experimental Algorithmics, Vol. 17, No. 2, Article 2.4, July 2012.
    By invitation to the special issue on selected papers from ALENEX 2010.
  • Bastian Degener, Joachim Gehweiler, and Christiane Lammersen (2010):
    Kinetic facility location.
    Algorithmica, 57(3): 562-584, July 2010.
    By invitation to the special issue on selected papers from SWAT 2008.

Konferenzartikel

  • Artur Czumaj, Christiane Lammersen, Morteza Monemizadeh, and Christian Sohler (2013):
    (1+ε)-approximation for facility location in data streams.
    In Proceedings of the 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2013), pp. 1710-1728.
  • Christiane Lammersen, Melanie Schmidt, and Christian Sohler (2012):
    Probabilistic k-median clustering in data streams.
    In Proceedings of the 10th Workshop on Approximation and Online Algorithms (WAOA 2012), pp. 70-81.
  • Marcel R. Ackermann, Christiane Lammersen, Marcus Märtens, Christoph Raupach, Christian Sohler, and Kamil Swierkot (2010):
    StreamKM++: A clustering algorithm for data streams.
    In Proceedings of the 12th Workshop on Algorithm Engineering and Experiments (ALENEX 2010), pp. 173-187.
    Invited to the special issue on selected papers from ALENEX 2010, submitted to ACM Journal on Experimental Algorithmics.
  • Christiane Lammersen, Anastasios Sidiropoulos, and Christian Sohler (2009):
    Streaming embeddings with slack.
    In Proceedings of the 11th Algorithms and Data Structures Symposium (WADS 2009), pp. 483-494.
  • Christiane Lammersen and Christian Sohler (2008):
    Facility location in dynamic geometric data streams.
    In Proceedings of the 16th Annual European Symposium on Algorithms (ESA 2008), pp. 660-671.
  • Bastian Degener, Joachim Gehweiler, and Christiane Lammersen (2008):
    The kinetic facility location problem.
    In Proceedings of the 11th Scandinavian Workshop on Algorithm Theory (SWAT 2008), pp. 378-389.
  • Joachim Gehweiler, Christiane Lammersen, and Christian Sohler (2006):
    A distributed O(1)-approximation algorithm for the uniform facility location problem.
    In Proceeedings of 18th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2006), pp. 237-243.

Papiere auf Workshops und Manuskripte

  • Bastian Degener, Joachim Gehweiler, and Christiane Lammersen (2008):
    The Kinetic Facility Location Problem.
    In Proceedings of the 24th European Workshop on Computational Geometry (EuroCG 2008), pp. 251-254.
  • Christiane Lammersen and Christian Sohler (2007):
    StrSort Algorithms for Geometric Problems.
    In Proceedings of the 23rd European Workshop on Computational Geometry (EWCG 2007), pp. 69-72.

Arbeiten

  • Christiane Lammersen (2010):
    Approximation Techniques for Facility Location and Their Applications in Metric Embeddings.
    Dissertation, Technische Universität Dortmund.
  • Christiane Lammersen (2005):
    Algorithmen für geometrische Probleme im Datenstrom-Modell erweitert um ein Sortierungsprimitiv.
    Diplomarbeit, Universität Paderborn.
  • Christiane Lammersen und Julia Seifert (2003):
    Modellierung der Farbsehfähigkeiten.
    Studienarbeit, Universität Paderborn.