FedSiKD: Clients Similarity and Knowledge Distillation: Addressing Non-i.i.d. and Constraints in Federated Learning

Documenti analoghi

• FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
  di: Jing, Shusen, et al.
  Pubblicazione: (2024)
• FedGraph-VASP: Privacy-Preserving Federated Graph Learning with Post-Quantum Security for Cross-Institutional Anti-Money Laundering
  di: Commey, Daniel, et al.
  Pubblicazione: (2026)
• Federated Learning on Non-iid Data via Local and Global Distillation
  di: Zheng, Xiaolin, et al.
  Pubblicazione: (2023)
• ISFL: Federated Learning for Non-i.i.d. Data with Local Importance Sampling
  di: Zhu, Zheqi, et al.
  Pubblicazione: (2022)
• Linear Bandits with Non-i.i.d. Noise
  di: Abélès, Baptiste, et al.
  Pubblicazione: (2025)