665 citations · 4.5k across the 236 of their papers we have counts for
12 papers · 1 filter
sDREAMER: Self-distilled Mixture-of-Modality-Experts Transformer for Automatic Sleep Staging
Jingyuan Chen, Yuan Yao, Mie Anderson +5
Automatic sleep staging based on electroencephalography (EEG) and electromyography (EMG) signals is an important aspect of sleep-related research. Current sleep staging methods suf…
FeDXL: Provable Federated Learning for Deep X-Risk Optimization
Zhishuai Guo, Rong Jin, Jiebo Luo +1
In this paper, we tackle a novel federated learning (FL) problem for optimizing a family of X-risks, to which no existing FL algorithms are applicable. In particular, the objective…
Remote Medication Status Prediction for Individuals with Parkinson's Disease using Time-series Data from Smartphones
Weijian Li, Wei Zhu, E. Ray Dorsey +1
Medication for neurological diseases such as the Parkinson's disease usually happens remotely away from hospitals. Such out-of-lab environments pose challenges in collecting timely…
Automatic Relation-aware Graph Network Proliferation
Shaofei Cai, Liang Li, Xinzhe Han +3
Graph neural architecture search has sparked much attention as Graph Neural Networks (GNNs) have shown powerful reasoning capability in many relational tasks. However, the currentl…
Localized Adversarial Domain Generalization
Wei Zhu, Le Lu, Jing Xiao +3
Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attent…
Deep Federated Anomaly Detection for Multivariate Time Series Data
Wei Zhu, Dongjin Song, Yuncong Chen +6
Despite the fact that many anomaly detection approaches have been developed for multivariate time series data, limited effort has been made on federated settings in which multivari…
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network
Jian Kang, Yan Zhu, Yinglong Xia +2
Graph Convolutional Network (GCN) plays pivotal roles in many real-world applications. Despite the successes of GCN deployment, GCN often exhibits performance disparity with respec…
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting
Wei Zhu, Jiebo Luo, Andrew White
Chemistry research has both high material and computational costs to conduct experiments. Institutions thus consider chemical data to be valuable and there have been few efforts to…
Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization
Wei Zhu, Haitian Zheng, Haofu Liao +2
Deep learning algorithms mine knowledge from the training data and thus would likely inherit the dataset's bias information. As a result, the obtained model would generalize poorly…
From Static to Dynamic Prediction: Wildfire Risk Assessment Based on Multiple Environmental Factors
Tanqiu Jiang, Sidhant K. Bendre, Hanjia Lyu +1
Wildfire is one of the biggest disasters that frequently occurs on the west coast of the United States. Many efforts have been made to understand the causes of the increases in wil…
Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data
Weijian Li, Wei Zhu, E. Ray Dorsey +1
Parkinsons Disease is a neurological disorder and prevalent in elderly people. Traditional ways to diagnose the disease rely on in-person subjective clinical evaluations on the qua…
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning
Zhongjie Yu, Lin Chen, Zhongwei Cheng +1
The successful application of deep learning to many visual recognition tasks relies heavily on the availability of a large amount of labeled data which is usually expensive to obta…