Titlebook: Machine Learning and Knowledge Discovery in Databases. Research Track; European Conference, Albert Bifet,Jesse Davis,Indr? ?liobait? Confer

NAG

Fast-FedUL: A Training-Free Federated Unlearning with?Provable Skew Resilienceincreasing demand to address issues such as “the right to be forgotten” and combat data poisoning attacks highlights the importance of techniques, known as ., which facilitate the removal of specific training data from trained FL models. Despite numerous unlearning methods proposed for centralized l

聯(lián)邦

Input Compression with?Positional Consistency for?Efficient Training and?Inference of?Transformer Nements for both training and inference, and are prone to overfitting on small data sets. To address these challenges, we present Input Compression with Positional Consistency (.), a new data augmentation method that simultaneously improves both generalization and training efficiency. The key insight