5 papers
Rethinking the Potential of Layer Freezing for Efficient DNN Training
Chence Yang, Ci Zhang, Lei Lu +11
With the growing size of deep neural networks and datasets, the computational costs of training have significantly increased. The layer-freezing technique has recently attracted gr…
Multimodal Cardiovascular Risk Profiling Using Self-Supervised Learning of Polysomnography
Zhengxiao He, Huayu Li, Geng Yuan +4
Methods: We developed a self-supervised deep learning model that extracts meaningful patterns from multi-modal signals (Electroencephalography (EEG), Electrocardiography (ECG), and…
Smarter Together: Combining Large Language Models and Small Models for Physiological Signals Visual Inspection
Huayu Li, Zhengxiao He, Xiwen Chen +8
Large language models (LLMs) have shown promising capabilities in visually interpreting medical time-series data. However, their general-purpose design can limit domain-specific pr…
Improving GPU Multi-Tenancy Through Dynamic Multi-Instance GPU Reconfiguration
Tianyu Wang, Sheng Li, Bingyao Li +6
Continuous learning (CL) has emerged as one of the most popular deep learning paradigms deployed in modern cloud GPUs. Specifically, CL has the capability to continuously update th…
MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features
Huayu Li, Ana S. Carreon-Rascon, Xiwen Chen +2
Medical time series data are indispensable in healthcare, providing critical insights for disease diagnosis, treatment planning, and patient management. The exponential growth in d…