Summary of Lolafl: Low-latency Federated Learning Via Forward-only Propagation, by Jierui Zhang et al.
LoLaFL: Low-Latency Federated Learning via Forward-only Propagation
by Jierui Zhang, Jianhao Huang, Kaibin Huang
First submitted to arxiv on: 19 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Networking and Internet Architecture (cs.NI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper tackles the challenge of low-latency federated learning (FL) in sixth-generation (6G) mobile networks. Traditional FL with deep neural networks and backpropagation is insufficient for meeting these requirements due to high-dimensional model parameters and numerous communication rounds. To address this, the authors introduce a novel framework called LoLaFL, which utilizes forward-only propagation and layer-wise transmissions and aggregation to significantly reduce latency. Additionally, two nonlinear aggregation schemes are proposed: one based on harmonic-mean-like parameter aggregation and another that exploits low-rank structures of features. Theoretical analysis and experiments demonstrate the effectiveness of LoLaFL in reducing latency while maintaining comparable accuracies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Federated learning is a way for devices to learn together without sharing their data. But traditional federated learning with deep neural networks doesn’t work well in 6G mobile networks because it takes too long. To fix this, the authors created a new approach called LoLaFL that sends and combines information more efficiently. This makes it much faster while still getting good results. They also came up with two ways to combine information even better: one that averages things out and another that uses special features. |
Keywords
» Artificial intelligence » Backpropagation » Federated learning
