3 papers
cs.LG2026
IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation
Mingchun Sun, Rongqiang Zhao, Muhammad Abdul Munnaf +1
In wireless sensor networks (WSNs), data augmentation is a novel method to improve sampling-frequency decision performance, thereby enabling energy optimization for IoT (Internet o…
cs.LG2026
IT-OSE: Exploring Optimal Sample Size for Industrial Data Augmentation
Mingchun Sun, Rongqiang Zhao, Zhennan Huang +2
In industrial scenarios, data augmentation is an effective approach to improve model performance. However, its benefits are not unidirectionally beneficial. There is no theoretical…
cs.LG2025
DS-Diffusion: Data Style-Guided Diffusion Model for Time-Series Generation
Mingchun Sun, Rongqiang Zhao, Hengrui Hu +2
Diffusion models are the mainstream approach for time series generation tasks. However, existing diffusion models for time series generation require retraining the entire framework…