Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning

Documenti analoghi

• An Adaptor for Triggering Semi-Supervised Learning to Out-of-Box Serve Deep Image Clustering
  di: Duan, Yue, et al.
  Pubblicazione: (2025)
• Decomposing and Composing: Towards Efficient Vision-Language Continual Learning via Rank-1 Expert Pool in a Single LoRA
  di: Fa, Zhan, et al.
  Pubblicazione: (2026)
• Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation
  di: Ma, Qinghe, et al.
  Pubblicazione: (2024)
• Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data
  di: Roy, Shuvendu, et al.
  Pubblicazione: (2023)
• Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers
  di: Kong, Heejo, et al.
  Pubblicazione: (2025)