3 papers
cs.LG2026
When Generator Replay Degrades: Projected Rehearsal Orchestration for Heterogeneous Federated Class-Incremental Learning
Thinh T. H. Nguyen, Khoa D. Doan, Binh T. Nguyen +2
Federated class-incremental learning (FCIL) becomes substantially harder when clients observe different label subsets, progress through tasks at different stages, and provide uneve…
cs.LG2026
HERO: A Heterogeneity-Aware Benchmark Library for Federated Continual Learning
Thinh T. H. Nguyen, Le-Tuan Nguyen, Minh-Duong Nguyen +4
Federated continual learning (FCL) evaluates how distributed clients learn from changing data streams while retaining previously learned knowledge. Existing evaluations are difficu…
cs.LG2025
Sequence Transferability and Task Order Selection in Continual Learning
Thinh Nguyen, Cuong N. Nguyen, Quang Pham +4
In continual learning, understanding the properties of task sequences and their relationships to model performance is important for developing advanced algorithms with better accur…