2 papers
stat.ML2026
Chaos Is a LADDER: Domain Generalization Beyond Invariance via Reweighting
Yuhang Jiang, Fengchuan Zhang, Sanguo Zhang +1
Domain generalization (DG) aims to learn from multiple source domains and generalize to unseen target domains. Most DG methods pursue invariance: they seek a causal representation…
cs.LG2025
Enhancing Federated Class-Incremental Learning via Spatial-Temporal Statistics Aggregation
Zenghao Guan, Guojun Zhu, Yucan Zhou +4
Federated Class-Incremental Learning (FCIL) enables Class-Incremental Learning (CIL) from distributed data. Existing FCIL methods typically integrate old knowledge preservation int…