Shiori Sagawa | DeepAI

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Featured Co-authors

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∙ 08/02/2023

OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

We introduce OpenFlamingo, a family of autoregressive vision-language mo...

0 Anas Awadalla, et al. ∙

∙ 02/23/2023

Out-of-Domain Robustness via Targeted Augmentations

Models trained on one set of domains often suffer performance drops on u...

0 Irena Gao, et al. ∙

∙ 12/09/2021

Extending the WILDS Benchmark for Unsupervised Adaptation

Machine learning systems deployed in the wild are often trained on a sou...

17 Shiori Sagawa, et al. ∙

∙ 07/19/2021

Just Train Twice: Improving Group Robustness without Training Group Information

Standard training via empirical risk minimization (ERM) can produce mode...

12 Evan Zheran Liu, et al. ∙

∙ 07/09/2021

Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization

For machine learning systems to be reliable, we must understand their pe...

0 John Miller, et al. ∙

∙ 12/14/2020

WILDS: A Benchmark of in-the-Wild Distribution Shifts

Distribution shifts can cause significant degradation in a broad range o...

11 Pang Wei Koh, et al. ∙

∙ 10/27/2020

Selective Classification Can Magnify Disparities Across Groups

Selective classification, in which models are allowed to abstain on unce...

0 Erik Jones, et al. ∙

∙ 05/09/2020

An Investigation of Why Overparameterization Exacerbates Spurious Correlations

We study why overparameterization – increasing model size well beyond th...

0 Shiori Sagawa, et al. ∙

∙ 11/20/2019

Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Overparameterized neural networks can be highly accurate on average on a...

0 Shiori Sagawa, et al. ∙

∙ 10/21/2019

Multi-Resolution Weak Supervision for Sequential Data

Since manually labeling training data is slow and expensive, recent indu...

16 Frederic Sala, et al. ∙

∙ 09/04/2019

Distributionally Robust Language Modeling

Language models are generally trained on data spanning a wide range of t...

0 Yonatan Oren, et al. ∙

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