The Data Analytics Laboratory investigates topics related to data analysis and organization at large scale. We are especially interested in machine learning, natural language processing and understanding, data mining and information retrieval. In all of these areas, the combination of well-informed theoretical models empowered by large-scale resources allows for exciting insights and applications.

recent publications

Active Content-Based Crowdsourcing Task Selection

  • authors P. Bansal, C. Eickhoff and T. Hofmann
  • published In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM), 2016

Privacy Leakage through Innocent Content Sharing in Online Social Networks

  • authors M. Han Veiga, C. Eickhoff
  • published In Proceedings of the ACM SIGIR Workshop on Privacy Preserving Information Retrieval, 2016

Implicit Negative Feedback in Clinical Information Retrieval

  • authors L. Kuhn and C. Eickhoff
  • published In Proceedings of the ACM SIGIR Medical Information Retrieval (MedIR) Workshop, 2016

Retrieval Techniques for Contextual Learning

  • authors N. Weingart and C. Eickhoff
  • published In Proceedings of the ACM SIGIR Search as Learning Workshop (SAL), 2016

Efficient Parallel Learning of Word2Vec

  • authors J. Vuurens, C. Eickhoff, A.P. de Vries
  • published In ICML 2016 ML Systems Workshop

Starting Small - Learning with Adaptive Sample Sizes

  • authors H. Daneshmand, A. Lucchi, T. Hofmann
  • published In International Conference on Machine Learning (ICML), 2016

Primal-Dual Rates and Certificates

  • authors C. Dünner, S. Forte, M. Takáč, M. Jaggi
  • published In International Conference on Machine Learning (ICML), 2016

A Cross-Platform Collection of Social Network Profiles

  • authors M. Han Veiga, C. Eickhoff
  • published In Proceedings of the 39th ACM Conference on Research and Development in Information Retrieval (SIGIR), 2016

Robust Statistical Methods in Web Retrieval

  • authors C. Eickhoff, A. P. de Vries
  • published In ACM SIGWEB Newsletter, Issue Winter, 2016
all publications

latest news


And the Qualcomm Fellowship 2016 goes to...

We are very pleased to announce that our PhD student Jason Lee was awarded a Qualcomm Fellowship 2016! Jason joined the lab in November 2015 and currently works on a unified neural language model for morphology grammar and coherence. Each winner will be awarded a 40,000 USD fellowship and receive mentorship from Qualcomm engineers.


Best Text Sentiment Analysis

Our lab's master students Jan Deriu and Maurice Gonzenbach won the 2016 SemEval text sentiment classification competition, placing first out of 34 teams from 24 countries. Maurice and Jan are supervized by Fatih Uzdilli, Valeria De Luca, Aurelien Lucchi and Martin Jaggi.


ACM SIGIR Best Paper

Carsten Eickhoff, Sebastian Dungs and Vu Tran receive an ACM SIGIR Best Paper Award honorable mention for their paper 'An Eye-tracking Study of Query Reformulation'.


GamifIR 2015 Best Presentation Award

Carsten Eickhoff receives along with Ragnhild Eg the GamifIR 'Best Presentation Award' at the 36th European Conference on Information Retrieval in Vienna, Austria.


Keynote at GamifIR'15

Carsten Eickhoff will give the keynote address at the Workshop on Gamification for Information Retrieval at ECIR in Vienna, Austria.


Vom Monopol auf Daten ist abzuraten

Big Data ist Big Business. Die Sammlung und die Verknüpfung von Informationen über Menschen im Netz bringen Milliarden ein. Und die Methoden werden immer abgefeimter und perfekter. Es ist Zeit, dagegen vorzugehen. Ein Artikel von Prof. Thomas Hofmann und Prof. Bernhard Schölkopf.

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