1 citations · 1 across the 5 of their papers we have counts for
5 papers
DRAUN: An Algorithm-Agnostic Data Reconstruction Attack on Federated Unlearning Systems
Hithem Lamri, Manaar Alam, Haiyan Jiang +1
Federated Unlearning (FU) enables clients to remove the influence of specific data from a collaboratively trained shared global model, addressing regulatory requirements such as GD…
Learning Long Short-Term Intention within Human Daily Behaviors
Zhe Sun, Rujie Wu, Xiaodong Yang +4
In the domain of autonomous household robots, it is of utmost importance for robots to understand human behaviors and provide appropriate services. This requires the robots to poss…
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow
Haiyan Jiang, Haoyi Xiong, Dongrui Wu +2
Principal component analysis (PCA) has been widely used as an effective technique for feature extraction and dimension reduction. In the High Dimension Low Sample Size (HDLSS) sett…
Robust Matrix Factorization with Grouping Effect
Haiyan Jiang, Shuyu Li, Luwei Zhang +2
Although many techniques have been applied to matrix factorization (MF), they may not fully exploit the feature structure. In this paper, we incorporate the grouping effect into MF…
Feature Grouping and Sparse Principal Component Analysis with Truncated Regularization
Haiyan Jiang, Shanshan Qin, Oscar Hernan Madrid Padilla
In this paper, we consider a new variant for principal component analysis (PCA), aiming to capture the grouping and/or sparse structures of factor loadings simultaneously. To achie…