Search Results for author:
Found 3 papers, 2 papers with code
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning
In this field, Data-Free Knowledge Transfer (DFKT) plays a crucial role in addressing catastrophic forgetting and data privacy problems.
NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation
In this paper, we propose a novel Noisy Layer Generation method (NAYER) which relocates the random source from the input to a noisy layer and utilizes the meaningful constant label-text embedding (LTE) as the input.
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization
Motivated by this analysis, we introduce our algorithm, Riemannian Sharpness-Aware Minimization (RSAM).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
