Efficient Machine Learning for Natural Language Processing - Detailseite

A current focus in Natural Language Processing (NLP) research is on efficient machine learning along several dimensions: (1) Sample-efficient learning - also known as few-shot learning - are machine learning approaches that require fewer data to train. (2) Parameter-efficient approaches seek to lower the computational requirements of fine-tuning large models. In this seminar, students will read current research papers and present them to each other. To pass the seminar, students should actively participate and give a presentation on their topic to the rest of the group.

Requirements:
- Students should have successfully passed the course "Introduction to NLP" to enroll in this seminar.

Daten- und Wissensmanagement.

Die LV findet in Englisch statt.