UMIACS
LSLT: Upon Reflection. This semester, we've asked presenters to give reflective talks about their most prominent work from the past. How did they understand the question then, and how do they see it now? See the full lineup here! Lunch will be served starting at 12:15. Vegetarian options available. Let us know if you have other dietary restrictions!
This week: Jordan Boyd-Graber, Associate Professor in Computer Science, UMIACS, and LSC
Computational models of language acquisition: Lessons from humans for machines and from machines for humans
Curriculum Learning: Scores, Plans, Dynamics, and NLP
Abstract: Curriculum learning is an effective and natural strategy in human learning. It plays an important role in challenging tasks such as language learning. However, current machine learning (ML) paradigms are mostly built upon repeatedly practicing the same training data/tasks with a random order, which is non-adaptive to the learning process. Moreover, they do not plan multiple learning stages in advance as humans.
Zoom link: https://umd.zoom.us/j/98806584197?pwd=SXBWOHE1cU9adFFKUmN2UVlwUEJXdz09 (passcode if needed: clip)
Scaling health care delivery with machine learning
Prof. Riedl will present virtually.
Zoom link: https://umd.zoom.us/j/98806584197?pwd=SXBWOHE1cU9adFFKUmN2UVlwUEJXdz09 (passcode if needed: clip)
The Quest for Automated Story Generation
Dr. Wang will present in person.
Zoom link: https://umd.zoom.us/j/98806584197?pwd=SXBWOHE1cU9adFFKUmN2UVlwUEJXdz09 (passcode if needed: clip)
Designing Human-Centered AI Systems for Human-AI Collaboration
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