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Found 4 papers, 2 papers with code
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
In this paper, we propose a novel Shapelet Transformer (ShapeFormer), which comprises class-specific and generic transformer modules to capture both of these features.
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).
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