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

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

Probabilistic Local Expert Retrieval

  • authors W. Li, C. Eickhoff, A. P. de Vries
  • published In Proceedings of the 38th European Conference on Information Retrieval (ECIR), 2016

Variance Reduced Stochastic Gradient Descent with Neighbors

  • authors T. Hofmann, A. Lucchi, S. Lacoste-Julien, B. McWilliams
  • published In Neural Information Processing Systems (NIPS), 2015

On the Global Linear Convergence of Frank-Wolfe Optimization Variants

  • authors S. Lacoste-Julien and M. Jaggi
  • published In Neural Information Processing Systems (NIPS), 2015

Eye-tracking Studies of Query Intent and Reformulation

  • authors C. Eickhoff, S. Dungs and V. Tran
  • published In Proceedings of the 14th Dutch-Belgian Information Retrieval Workshop (DIR), 2015
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.

all news