Dataset Release for Evaluation of Counterfactual Algorithms

Criteo Research is pleased to announce the release of a new dataset to serve as a large-scale standardized test-bed for the evaluation of counterfactual learning methods. Criteo Research has access to several large-scale, real-world datasets that they would like to share with the external research community with the goal of both advancing research and facilitating an easier exchange of ideas. The dataset they are releasing has been prepared in partnership with Cornell University (Thorsten Joachim’s group) and the University of Amsterdam (ILPS). Continue reading

FAT/WEB: Workshop on Fairness, Accountability, and Transparency on the Web

www2017_logoRecent academic and journalistic reviews of online web services have revealed that many systems exhibit subtle biases reflecting historic discrimination. Examples include racial and gender bias in search advertising, image recognition services, sharing economy mechanisms, pricing, and web-based delivery. The list of production systems exhibiting biases continues to grow and may be endemic to the way models are trained and the data used. Continue reading

SEA: Search Engines Amsterdam on December 16

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This edition of SEA is in partnership with FNWI. We will have two talks followed by drinks. The academic talk will be given by Maria Eskevich from Radboud University and the industry talk will be given by Gerbert Kaandorp from BrainCreators.com. Please note that this edition of SEA will be held in the Universiteitsbiblioth­eek (Vondelzaal), Singel 425, 1012WP, Amsterdam. Continue reading

Nikos Voskarides Wins KION AI Thesis Award

logo-uvaCongratulations to ILPS PhD student Nikos Voskarides for winning the KION AI Thesis Award for his MSc thesis “Explaining relationships between entities.” The prize was awarded today, November 10, 2016, at BNAIC 2016 in Amsterdam. His MSc thesis was supervised by Edgar Meij and Manos Tsagkias and a paper based on the thesis was presented at ACL 2015 in Beijing, with follow-up currently under submission.