FREDERIC SALA
fredsala@cs.wisc.edu
I study the fundamentals of data-driven systems and machine learning.
Much of my current work focuses on foundation models, automated machine learning, learning with limited data, and geometric machine learning.
I have a research leadership role at Snorkel AI, where we are building a data-first approach to AI.
Previously, I was a postdoc in Stanford CS, associated with the Hazy group. I completed my Ph.D. in electrical engineering at UCLA, where I worked with the LORIS and StarAI groups.
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Students
Graduate Students
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Publications
Conference | Journal | Preprint | Workshop
2024
2023
Understanding Threshold-based Auto-labeling: The Good, the Bad, and the Terra Incognita
Harit Vishwakarma, Frederic Sala, Ramya Vinayak
NeurIPS Workshop on Adaptive Experimental Design and Active Learning in the Real World (RealML-2023), 2023
Mixed Curvature Representation Learning for Biological Pathway Graphs
Daniel McNeela, Frederic Sala, Anthony Gitter
ICML Workshop for Computational Biology, 2023
2022
AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels
Nicholas Roberts, Xintong Li, Tzu-Heng Huang, Dyah Adila, Spencer Schoenberg, Cheng-Yu Liu, Lauren Pick, Haotian Ma, Aws Albarghouthi, Frederic Sala
Neural Information Processing Systems (NeurIPS) (Datasets and Benchmarks Track), 2022
arXiv | OpenReview | code
AutoML for Climate Change: A Call to Action
Renbo Tu, Nicholas Roberts, Vishak Prasad, Sibasis Nayak, Paarth Jain, Frederic Sala, Ganesh Ramakrishnan, Ameet Talwalkar, Willie Neiswanger, Colin White
NeurIPS 2022 Workshop on Tackling Climate Change with Machine Learning, 2022
arXiv
2021
2020
2019
Multi-Resolution Weak Supervision for Sequential Data
Frederic Sala*, Paroma Varma*, Shiori Sagawa, Jason Fries, Daniel Y. Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré.
Neural Information Processing Systems (NeurIPS), 2019
paper
older
2018
2017
2016
paper
2015 and older
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Awards
- Best Paper Award Honorable Mention, NeurIPS R0-FoMo Workshop, 2023
- Best Student Paper Runner-Up, UAI, 2022
- Outstanding Ph.D. Dissertation Award, UCLA Department of Electrical Engineering
- UCLA Dissertation Year Fellowship
- Qualcomm Innovation Fellowship Finalist
- Edward K. Rice Outstanding Masters Student Award UCLA Henry Samueli School of Engineering & Applied Science
- Outstanding M.S. Thesis Award, UCLA Department of Electrical Engineering
- National Science Foundation Graduate Research Fellowship (NSF GRFP)
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