Show simple item record

dc.contributor.authorLarochelle, Hugo
dc.date.accessioned2018-10-30T21:15:33Z
dc.date.available2018-10-30T21:15:33Z
dc.date.issued2018-10-15
dc.identifier.urihttp://hdl.handle.net/1853/60506
dc.descriptionPresented on October 15, 2018 at 12:15 pm in the Marcus Nanotechnology Building, Rooms 1116.en_US
dc.descriptionHugo Larochelle is a Research Scientist at Google Brain and lead of the Montreal Google Brain team. Larochelle also co-founded Whetlab, which was acquired in 2015 by Twitter, where he then worked as a Research Scientist in the Twitter Cortex group.en_US
dc.descriptionRuntime: 63:15 minutesen_US
dc.description.abstractA lot of the recent progress on many AI tasks enabled in part by the availability of large quantities of labeled data. Yet, humans are able to learn concepts from as little as a handful of examples. Meta-learning is a very promising framework for addressing the problem of generalizing from small amounts of data, known as few-shot learning. In meta-learning, our model is itself a learning algorithm: it takes input as a training set and outputs a classifier. For few-shot learning, it is (meta-)trained directly to produce classifiers with good generalization performance for problems with very little labeled data. In this talk, I'll present an overview of the recent research that has made exciting progress on this topic (including my own) and will discuss the challenges as well as research opportunities that remain.en_US
dc.format.extent63:15 minutes
dc.language.isoen_USen_US
dc.relation.ispartofseriesMachine Learning@Georgia Tech Seminar Seriesen_US
dc.subjectDeep learningen_US
dc.subjectFew-shot learningen_US
dc.subjectMeta-learningen_US
dc.titleFew-shot Learning with Meta-Learning: Progress Made and Challenges Aheaden_US
dc.typeLectureen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Machine Learningen_US
dc.contributor.corporatenameGoogle Brainen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record