Search Results for author: Shelby Williams

Found 2 papers, 1 papers with code

FedFair^3: Unlocking Threefold Fairness in Federated Learning

no code implementations • 29 Jan 2024 • Simin Javaherian, Sanjeev Panta, Shelby Williams, Md Sirajul Islam, Li Chen

In addition to having a fair client-selection strategy, we enforce an equitable number of rounds for client participation and ensure a fair accuracy distribution over the clients.

Fairness Federated Learning

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MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformer

1 code implementation • ICCV 2023 • Fudong Lin, Summer Crawford, Kaleb Guillot, Yihe Zhang, Yan Chen, Xu Yuan, Li Chen, Shelby Williams, Robert Minvielle, Xiangming Xiao, Drew Gholson, Nicolas Ashwell, Tri Setiyono, Brenda Tubana, Lu Peng, Magdy Bayoumi, Nian-Feng Tzeng

In this work, we develop a deep learning-based solution, namely Multi-Modal Spatial-Temporal Vision Transformer (MMST-ViT), for predicting crop yields at the county level across the United States, by considering the effects of short-term meteorological variations during the growing season and the long-term climate change on crops.

Contrastive Learning Crop Yield Prediction +1

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