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Nathan Stromberg
About me
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Posts
Recognized as a Horejsi Scholar by the ARCS Foundation
Published:
I am excited to announce that I was selected by the ARCS Foundation as a 2025-2026 Horejsi Scholar. This is a fantastic honor and validates the importance of our work in fair and robust machine learning. I am extremely grateful to the ARCS Foundation and Mr. Stewart Horejsi whose generous donation made the award possible.
Paper Accepted to TMLR
Published:
I am happy to announce that my paper entitled “Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains” has been accepted to the Transactions on Machine Learning Research (TMLR). It’s a nice work that introduces a new two-stage last layer model intervention which encourages group-fair predictions without knowledge of the groups.
Papers Accepted to NeurIPS 2024
Published:
I am excited to announce that a paper on which I am first author was accepted to NeurIPS 2024. I am grateful to my collaborators: Rohan Ayyagari (ASU), Monica Welfert (ASU), Sanmi Koyejo (Stanford), Richard Nock (Google), and Lalitha Sankar (ASU). It is a really cool work on making state-of-the-art fairness interventions robust to labels noise. Find the paper here. I am looking forward to meeting with some fantastic (future) collaborators!
portfolio
Portfolio item number 1
Published:
Short description of portfolio item number 1
Portfolio item number 2
Published:
Short description of portfolio item number 2
publications
Smoothly Giving Up: Robustness for Simple Models
Published in AISTATS 2023, 2023
Boosting with $\alpha$-loss and its application to simple models
Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains
Published in TMLR, 2024
Robust worst-group accuracy via biased pseudo-annotation
Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
Published in ISIT 2024, 2024
Theoretical comparison of several popular WGA correction methods for LLR
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading
Published in NeurIPS 2024, 2024
Cleaning labels to improve robustness of two-stage corrections
talks
Smoothly Giving Up: Robustness for Simple Models
Published:
Talk given as a part of AISTATS 2023. The talk can be found here and the relevant paper can be found here
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.