Teacher-student Networks for Multilingual Adaptation (Chen et al. 2017)
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Types of Multi-tasking
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Multiple Annotation Standards
Description:
Explore multilingual and multitask learning in neural networks for natural language processing through this 52-minute lecture by Graham Neubig. Delve into key concepts such as multitask learning, domain adaptation, and multilingual learning. Gain insights on increasing data through multitask approaches, pre-training encoders, and regularization techniques. Examine supervised and unsupervised domain adaptation methods, multilingual inputs and outputs, and teacher-student networks for multilingual adaptation. Understand various types of multi-tasking and multiple annotation standards in NLP tasks. Access accompanying slides and related course materials for a comprehensive learning experience in advanced NLP techniques.
Neural Nets for NLP 2017 - Multilingual and Multitask Learning