Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction

Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction

Item #:: 075280-1131
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DOI: https://doi.org/10.52202/075280-1131
Author(s): Hanhan Zhou, Tian Lan, Guru Prasadh Venkataramani, Wenbo Ding
Pages: 25991-26002 (12 pages)
Format: PDF Paper Download
Conference: Advances in Neural Information Processing Systems 36
Date/Location: Held 10-16 December 2023, New Orleans, Louisiana, USA.
Series: Advances in Neural Information Processing Systems 36
Publisher: Neural Information Processing Systems Foundation, Inc. (NeurIPS)

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DOI: https://doi.org/10.52202/075280-1131
Author(s): Hanhan Zhou, Tian Lan, Guru Prasadh Venkataramani, Wenbo Ding
Pages: 25991-26002 (12 pages)
Format: PDF Paper Download
Conference: Advances in Neural Information Processing Systems 36
Date/Location: Held 10-16 December 2023, New Orleans, Louisiana, USA.
Series: Advances in Neural Information Processing Systems 36
Publisher: Neural Information Processing Systems Foundation, Inc. (NeurIPS)