Summary of Gas: Generative Activation-aided Asynchronous Split Federated Learning, by Jiarong Yang and Yuan Liu
GAS: Generative Activation-Aided Asynchronous Split Federated Learningby Jiarong Yang, Yuan LiuFirst submitted to arxiv on:…
GAS: Generative Activation-Aided Asynchronous Split Federated Learningby Jiarong Yang, Yuan LiuFirst submitted to arxiv on:…
Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learningby Lucas Lange, Maurice-Maximilian Heykeroth,…
Federated Aggregation of Mallows Rankings: A Comparative Analysis of Borda and Lehmer Codingby Jin Sima,…
Compressing VAE-Based Out-of-Distribution Detectors for Embedded Deploymentby Aditya Bansal, Michael Yuhas, Arvind EaswaranFirst submitted to…
EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classificationby Ben DaiFirst submitted to arxiv…
Variation in prediction accuracy due to randomness in data division and fair evaluation using interval…
Defending against Model Inversion Attacks via Random Erasingby Viet-Hung Tran, Ngoc-Bao Nguyen, Son T. Mai,…
Bootstrap SGD: Algorithmic Stability and Robustnessby Andreas Christmann, Yunwen LeiFirst submitted to arxiv on: 2…
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalizationby Dingshuo Chen, Zhixun Li, Yuyan Ni, Guibin…
Knowledge-data fusion oriented traffic state estimation: A stochastic physics-informed deep learning approachby Ting Wang, Ye…