Stanford MLSys Seminar Episode 56: Fait Poms [Th, 1.35-2.30pm PT]

[Karan Goel]

Hi everyone,

We're back with the fifty-sixth episode of the MLSys Seminar on Thursday from 1.35-2.30pm PT. 

We'll be joined by Fait Poms, who will talk about interactive model development. The format is a 30 minute talk followed by a 30 minute podcast-style discussion, where the live audience can ask questions.

Livestream Link: https://www.youtube.com/watch?v=-9LbJBzK2HQ

Guests: Fait Poms

Title: A vision for interactive model development: efficient machine learning by bringing domain experts in the loop

Abstract: Building computer vision models today is an exercise in patience--days to weeks for human annotators to label data, hours to days to train and evaluate models, weeks to months of iteration to reach a production model. Without tolerance for this timeline or access to the massive compute and human resources required, building an accurate model can be challenging if not impossible. In this talk, we discuss a vision for interactive model development with iteration cycles of minutes, not weeks. We believe the key to this is integrating the domain expert at key points in the model building cycle and leveraging supervision cues above just example-level annotation. We will discuss our recent progress toward aspects of this goal: judiciously choosing when to use the machine and when to use the domain expert for fast, low label budget model training (CVPR 2021, ICCV 2021), building confidence in model performance with low-shot validation (ICCV 2021 Oral), and some initial tools for rapidly defining correctness criteria.
Bio: Fait Poms is a Ph.D. student at Stanford advised by Prof. Kayvon Fatahalian and a Senior Applied Research Scientist at Snorkel.AI. Her research concerns designing algorithms and systems that enable domain experts to rapidly define, train, and validate computer vision models for specialized tasks. She has done research internships at Snorkel AI (with Braden Hancock and Alex Ratner), Facebook Reality Labs (with Yaser Sheikh, Chenglei Wu, and Shoou-I Yu), and NVIDIA Research (with Michael Garland and Michael Bauer), and has transferred her research into production at Snorkel AI and Facebook. Her work has appeared at CVPR, ICCV, and SIGGRAPH. Website: https://faitpoms.com/

See you all there!

Best,

Karan

[Karan Goel]

Reminder: we're starting in 10 minutes!