2 citations · 5 across the 5 of their papers we have counts for
5 papers
Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal Dynamics
Liangwei Nathan Zheng, Zhengyang Li, Chang George Dong +5
Irregular Time Series Data (IRTS) has shown increasing prevalence in real-world applications. We observed that IRTS can be divided into two specialized types: Natural Irregular Tim…
Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment
Liangwei Nathan Zheng, Chang George Dong, Wei Emma Zhang +4
Large Language Models (LLMs) have demonstrated impressive performance in time series analysis and seems to understand the time temporal relationship well than traditional transform…
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
Shaofei Shen, Chenhao Zhang, Yawen Zhao +3
Machine unlearning aims to remove information derived from forgotten data while preserving that of the remaining dataset in a well-trained model. With the increasing emphasis on da…
CaMU: Disentangling Causal Effects in Deep Model Unlearning
Shaofei Shen, Chenhao Zhang, Alina Bialkowski +2
Machine unlearning requires removing the information of forgetting data while keeping the necessary information of remaining data. Despite recent advancements in this area, existin…
Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent
Guanhua Ye, Hongzhi Yin, Tong Chen +3
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learn…