Energy is now a primary constraint for modern machine-learning training and inference, from hyperscale data centers to battery-constrained edge devices. Prior surveys cover efficient and green deep learning, edge artificial intelligence (AI), accelerator architectures, lifecycle-level energy reduction, and measurement...
Zu-Xiong Tan, Ali Karkehabadi, Ning Miao et al.· IEEE Access· 0 citations
AMEND predicts each block's BLASST verdict from margins audited at earlier steps, so the GPU fetches only predicted survivors while near-bank PIM units in high-bandwidth memory (HBM) concurrently score the omitted complement.
Zu-Xiong Tan, Will Wei-Jen Wang, Wei Shao et al.· 0 citations
A lightweight low-rate wrist SPO2 estimation framework that integrates motion-aware beat selection and perfusion-guided calibration is proposed that achieves the best 25 Hz performance and reduces PPG sensor power consumption for energy-efficient wearable implementation.
Zequan Liang, Ning Miao, Wei Shao et al.· 0 citations
The results show that the dominant source of failure can shift across model generations, motivating evaluation that diagnoses where and why long-horizon security agents fail rather than relying only on aggregate task success.
Wei Shao, Chongzhou Fang, Zu-Xiong Tan et al.· 1 citation
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