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The success of today’s data-driven machine learning models is often strongly correlated with the amount of available high quality labeled data. For many applications, large-scale, high-quality training data is not available, which highlights the increasing need for building models with the ability to learn complex tasks with imperfect supervision, i.e., where the learning process is based on imperfect training samples. Mostafa Dehghani focuses on improving the process of learning with imperfect supervision, concentrating on language understanding and reasoning.

Event details of Machine learning for language understanding
Date 28 February 2020
Time 10:00 -11:00
Location Agnietenkapel

M. Dehghani: Learning with Imperfect Supervision for Language Understanding.


Prof. M. de Rijke

Dr J. Kamps


This event is open to the public.


Oudezijds Voorburgwal 229 - 231
1012 EZ Amsterdam