Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation
No confident code implementation found for this paper.
No confident code implementation found for this paper.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
Hyper-MD: Mesh Denoising with Customized Parameters Aware of Noise Intensity and Geometric Characteristics
On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms
INViTE: INterpret and Control Vision-Language Models with Text Explanations
LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion
Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models
@article{li2026analysis,
title = {Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation},
author = {Xiaoyun Li and Ping Li},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:62548eb2acb33174d618d3a7656c789ff1e4e4ed},
journal = {ICML 2023 2023}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/62548eb2acb33174d618d3a7656c789ff1e4e4ed)