most citedPrivate Gradient Estimation is Useful for Generative Modeling

1 citations · 1 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

cs.CV2026

Divide and Conquer: Static-Dynamic Collaboration for Few-Shot Class-Incremental Learning

Kexin Bao, Daichi Zhang, Yong Li +2

Few-shot class-incremental learning (FSCIL) aims to continuously recognize novel classes under limited data, which suffers from the key stability-plasticity dilemma: balancing the…

cs.CV2023★ 1 cited

Private Gradient Estimation is Useful for Generative Modeling

Bochao Liu, Pengju Wang, Weijia Guo +4

While generative models have proved successful in many domains, they may pose a privacy leakage risk in practical deployment. To address this issue, differentially private generati…