Summary of Seamless Integration: Sampling Strategies in Federated Learning Systems, by Tatjana Legler et al.
Seamless Integration: Sampling Strategies in Federated Learning Systemsby Tatjana Legler, Vinit Hegiste, Martin RuskowskiFirst submitted…
Summary of Addressing Heterogeneity in Federated Learning: Challenges and Solutions For a Shared Production Environment, by Tatjana Legler et al.
Addressing Heterogeneity in Federated Learning: Challenges and Solutions for a Shared Production Environmentby Tatjana Legler,…
Summary of Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation For Hierarchical Federated Learning, by Rung-hung Gau et al.
Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learningby…
Summary of A Hassle-free Algorithm For Private Learning in Practice: Don’t Use Tree Aggregation, Use Blts, by H. Brendan Mcmahan et al.
A Hassle-free Algorithm for Private Learning in Practice: Don’t Use Tree Aggregation, Use BLTsby H.…
Summary of Enhancing Object Detection with Hybrid Dataset in Manufacturing Environments: Comparing Federated Learning to Conventional Techniques, by Vinit Hegiste et al.
Enhancing Object Detection with Hybrid dataset in Manufacturing Environments: Comparing Federated Learning to Conventional Techniquesby…
Summary of Mitigating Backdoor Attacks in Federated Learning Via Flipping Weight Updates Of Low-activation Input Neurons, by Binbin Ding et al.
Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neuronsby Binbin…
Summary of A Multivocal Literature Review on Privacy and Fairness in Federated Learning, by Beatrice Balbierer et al.
A Multivocal Literature Review on Privacy and Fairness in Federated Learningby Beatrice Balbierer, Lukas Heinlein,…
Summary of Rbla: Rank-based-lora-aggregation For Fine-tuning Heterogeneous Models in Flaas, by Shuaijun Chen et al.
RBLA: Rank-Based-LoRA-Aggregation for Fine-tuning Heterogeneous Models in FLaaSby Shuaijun Chen, Omid Tavallaie, Niousha Nazemi, Albert…
Summary of The Power Of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacy, by Jiating Ma et al.
The Power of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacyby Jiating…
Summary of Random Gradient Masking As a Defensive Measure to Deep Leakage in Federated Learning, by Joon Kim et al.
Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learningby Joon Kim,…