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Found 7 papers, 1 papers with code
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models
In the absence of centralized data, Federated Learning (FL) can benefit from distributed and private data of the FL edge clients for fine-tuning.
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning
We show that this resource overhead is caused by an incorrect perspective in all prior work that treats an attack on an aggregate update in the same way as an individual update with a larger batch size.
LOKI: Large-scale Data Reconstruction Attack against Federated Learning through Model Manipulation
When both FedAVG and secure aggregation are used, there is no current method that is able to attack multiple clients concurrently in a federated learning setting.
Federated Analytics: A survey
Federated analytics (FA) is a privacy-preserving framework for computing data analytics over multiple remote parties (e. g., mobile devices) or silo-ed institutional entities (e. g., hospitals, banks) without sharing the data among parties.
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?
While SA ensures no additional information is leaked about the individual model update beyond the aggregated model update, there are no formal guarantees on how much privacy FL with SA can actually offer; as information about the individual dataset can still potentially leak through the aggregated model computed at the server.
Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training
As our main contribution, we propose Basil, a fast and computationally efficient Byzantine robust algorithm for decentralized training systems, which leverages a novel sequential, memory assisted and performance-based criteria for training over a logical ring while filtering the Byzantine users.
Secure Aggregation with Heterogeneous Quantization in Federated Learning
The state-of-the-art protocols for secure model aggregation, which are based on additive masking, require all users to quantize their model updates to the same level of quantization.
Information Theory Systems and Control Systems and Control Information Theory
