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 […]

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 […]

Share your Model instead of your Data!

Our paper "Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking", with Hosein Azarbonyad, Jaap Kamps, and Maarten de Rijke, has been accepted at Neu-IR: SIGIR Workshop on Neural Information Retrieval (NeuIR'17). \o/ Deep neural networks demonstrate undeniable success in several fields and employing them is taking o for information retrieval […]

On Search Powered Navigation

Our paper "On Search Powered Navigation", with Glorianna Jagfeld, Hosein Azarbonyad, Alex Olieman, Jaap Kamps, Maarten Marx, has been accepted as a short paper at The 3rd ACM International Conference on the Theory of Information Retrieval (ICTIR2017). \o/ Knowledge graphs and other hierarchical domain ontologies hold great promise for complex information seeking tasks, yet their […]

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 […]

Modeling Retrieval Problem using Neural Networks

Despite the buzz surrounding deep neural networks (DNN) models for information retrieval, the literature is still lacking a systematic basic investigation on how generally we can model the retrieval problem using neural networks. Modeling the retrieval problem in the context of neural networks means the general way that we frame the problem with regards to […]