2 citations · 7 across the 6 of their papers we have counts for
6 papers
Multimodal Federated Learning under Dual-Axis Modality Missingness
Adiba Orzikulova, Jaehyun Kwak, Jaemin Shin +5
Multimodal federated learning (FL) supports collaborative modeling in privacy-sensitive health-sensing and medical settings, but realistic deployments often exhibit dual-axis modal…
Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices
Shengyuan Ye, Liekang Zeng, Xiaowen Chu +2
On-device Deep Neural Network (DNN) training has been recognized as crucial for privacy-preserving machine learning at the edge. However, the intensive training workload and limite…
ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer's Disease
Xiaomin Ouyang, Xian Shuai, Yang Li +12
Alzheimer's Disease (AD) and related dementia are a growing global health challenge due to the aging population. In this paper, we present ADMarker, the first end-to-end system tha…
Miriam: Exploiting Elastic Kernels for Real-time Multi-DNN Inference on Edge GPU
Zhihe Zhao, Neiwen Ling, Nan Guan +1
Many applications such as autonomous driving and augmented reality, require the concurrent running of multiple deep neural networks (DNN) that poses different levels of real-time p…
Interpersonal Distance Tracking with mmWave Radar and IMUs
Yimin Dai, Xian Shuai, Rui Tan +1
Tracking interpersonal distances is essential for real-time social distancing management and {\em ex-post} contact tracing to prevent spreads of contagious diseases. Bluetooth neig…
Moses: Efficient Exploitation of Cross-device Transferable Features for Tensor Program Optimization
Zhihe Zhao, Xian Shuai, Yang Bai +4
Achieving efficient execution of machine learning models has attracted significant attention recently. To generate tensor programs efficiently, a key component of DNN compilers is…