DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models | ScienceToStartup | ScienceToStartup

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References (68)

[1]

Advances in Global Solvers for 3D Vision

2026Zhenjun Zhao, Heng Yang et al.

[2]

Enhancing News Classification: Domain-Specific Guided Pretraining Based on Adaptive Selective Masking

2026Qiao Ding, Heng Ding et al.

[3]

Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges

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DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models

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Founder's Pitch

"Optimizer enhancing privacy and performance in federated learning for language and vision models."

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DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models

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Founder's Pitch

"Optimizer enhancing privacy and performance in federated learning for language and vision models."

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