4 citations · 7 across the 4 of their papers we have counts for
9 papers
Federated Remote Physiological Measurement with Imperfect Data
Xin Liu, Mingchuan Zhang, Ziheng Jiang +2
The growing need for technology that supports remote healthcare is being acutely highlighted by an aging population and the COVID-19 pandemic. In health-related machine learning ap…
Automated Backend-Aware Post-Training Quantization
Ziheng Jiang, Animesh Jain, Andrew Liu +4
Quantization is a key technique to reduce the resource requirement and improve the performance of neural network deployment. However, different hardware backends such as x86 CPU, N…
SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices
Xin Liu, Yuang Li, Josh Fromm +4
Super-resolution (SR) is a coveted image processing technique for mobile apps ranging from the basic camera apps to mobile health. Existing SR algorithms rely on deep learning mode…
MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement
Xin Liu, Ziheng Jiang, Josh Fromm +3
There are large individual differences in physiological processes, making designing personalized health sensing algorithms challenging. Existing machine learning systems struggle t…
Just-in-Time Dynamic-Batching
Sheng Zha, Ziheng Jiang, Haibin Lin +1
Batching is an essential technique to improve computation efficiency in deep learning frameworks. While batch processing for models with static feed-forward computation graphs is s…
Relay: A High-Level Compiler for Deep Learning
Jared Roesch, Steven Lyubomirsky, Marisa Kirisame +7
Frameworks for writing, compiling, and optimizing deep learning (DL) models have recently enabled progress in areas like computer vision and natural language processing. Extending…