SIGIR2018 Workshop on Learning From Noisy/Limited Data for IR

We are organizing the "Learning From Noisy/Limited Data for Information Retrieval" workshop which is co-located with SIGIR 2018. This is the first edition of this workshop and The goal of the workshop is to bring together researchers from industry, where data is plentiful but noisy, with researchers from academia, where data is sparse but clean, to […]

Fidelity-Weighted Learning

Our paper "Fidelity-Weighted Learning", with Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schölkopf, has been accepted at Sixth International Conference on Learning Representations (ICLR2018). \o/ The success of deep neural networks to date depends strongly on the availability of labeled data which is costly and not always easy to obtain. Usually, it is much easier […]

Beating the Teacher: Neural Ranking Models with Weak Supervision

Our paper "Neural Ranking Models with Weak Supervision", with Hamed Zamani, Aliaksei Severyn, Jaap Kamps, and W. Bruce Croft, has been accepted as a long paper at The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017). \o/ This paper is on the outcome of my pet project during my internship […]