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 […]

Avoiding Your Teacher's Mistakes: Training Neural Networks with Controlled Weak Supervision

This post is about the project I've done in collaboration with Aliaksei Severyn, Sascha Rothe, and Jaap Kamps, during my internship at Google Research. Deep neural networks have shown impressive results in a lot of tasks in computer vision, natural language processing, and information retrieval. However, their success is conditioned on the availability of exhaustive […]

UvA at CIKM2017

CIKM2017's notifications are out. So there will be nine papers (full/short/demo/workshop) co-authored by our research group at the University of Amsterdam this year. To make it more convenient for those who are going to attend CIKM this year to follow up on our research, we decided to prepare a list of our contributions. I've designed a bookmark […]

Some Highlights of MILA Deep Learning and Reinforcement Learning Summer Schools 2017

A couple weeks a go, I attended MILLA Deep Learning summer school (DLSS) from June 26th to July 1st and Reinforcement Learning summer school (RLSS) from  July 3rd to 5th, 2017, organized by Yoshua Bengio and Aaron Courville. You can find information about the lectures here. In the following, I will share some of "my" highlights from […]

Learning to Attend, Copy, and Generate for Session-Based Query Suggestion

Our paper "Learning to Attend, Copy, and Generate for Session-Based Query Suggestion", with Sascha Rothe, Enrique Alfonseca, and Pascal Fleury, has been accepted as a long paper at the international Conference on Information and Knowledge Management (CIKM'17). This paper is on the outcome of my internship at Google Research. \o/ Users interact with search engines […]