55 citations · 58 across the 6 of their papers we have counts for
4 papers · 1 filter
A Comparative Study on How Data Normalization Affects Zero-Shot Generalization in Time Series Foundation Models
Ihab Ahmed, Denis Krompaß, Cheng Feng +1
We investigate input normalization methods for Time-Series Foundation Models (TSFMs). While normalization is well-studied in dataset-specific time-series models, it remains overloo…
Does Machine Unlearning Truly Remove Knowledge?
Haokun Chen, Yueqi Zhang, Yuan Bi +9
In recent years, Large Language Models (LLMs) have achieved remarkable advancements, drawing significant attention from the research community. Their capabilities are largely attri…
FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models
Haokun Chen, Hang Li, Yao Zhang +7
One-Shot Federated Learning (OSFL), a special decentralized machine learning paradigm, has recently gained significant attention. OSFL requires only a single round of client data o…
Few-Shot One-Class Classification via Meta-Learning
Ahmed Frikha, Denis Krompaß, Hans-Georg Köpken +1
Although few-shot learning and one-class classification (OCC), i.e., learning a binary classifier with data from only one class, have been separately well studied, their intersecti…