1 code implementation • 10 May 2023 • Chaoqi Yang, M. Brandon Westover, Jimeng Sun
Comprehensive evaluations on EEG, electrocardiogram (ECG), and human activity sensory signals demonstrate that \method outperforms robust baselines in common settings and facilitates learning across multiple datasets with different formats.
1 code implementation • 21 Jan 2023 • Chaoqi Yang, M. Brandon Westover, Jimeng Sun
Extensive experiments show that ManyDG can boost the generalization performance on multiple real-world healthcare tasks (e. g., 3. 7% Jaccard improvements on MIMIC drug recommendation) and support realistic but challenging settings such as insufficient data and continuous learning.
1 code implementation • 25 Jul 2022 • Junyi Gao, Chaoqi Yang, George Heintz, Scott Barrows, Elise Albers, Mary Stapel, Sara Warfield, Adam Cross, Jimeng Sun, the N3C consortium
We respond to the national Pediatric COVID-19 data challenge with a novel machine learning model, MedML.
1 code implementation • 8 May 2022 • Chaoqi Yang, Cheng Qian, Jimeng Sun
Our variant GOCPTE shows up to 1:2% and 5:5% fitness improvement on two datasets with about 20% speedup compared to the best model.
1 code implementation • 27 Oct 2021 • Chaoqi Yang, Danica Xiao, M. Brandon Westover, Jimeng Sun
Objective: In this paper, we aim to learn robust vector representations from massive unlabeled EEG signals, such that the learned vectorized features (1) are expressive enough to replace the raw signals in the sleep staging task; and (2) provide better predictive performance than supervised models in scenarios of fewer labels and noisy samples.
1 code implementation • 15 Jun 2021 • Chaoqi Yang, Cheng Qian, Navjot Singh, Cao Xiao, M Brandon Westover, Edgar Solomonik, Jimeng Sun
This paper addresses the above challenges by proposing augmented tensor decomposition (ATD), which effectively incorporates data augmentations and self-supervised learning (SSL) to boost downstream classification.
1 code implementation • 14 Jun 2021 • Chaoqi Yang, Navjot Singh, Cao Xiao, Cheng Qian, Edgar Solomonik, Jimeng Sun
Our MTC model explores tensor mode properties and leverages the hierarchy of resolutions to recursively initialize an optimization setup, and optimizes on the coupled system using alternating least squares.
no code implementations • 5 May 2021 • Chaoqi Yang, Cao Xiao, Fenglong Ma, Lucas Glass, Jimeng Sun
On a benchmark dataset, our SafeDrug is relatively shown to reduce DDI by 19. 43% and improves 2. 88% on Jaccard similarity between recommended and actually prescribed drug combinations over previous approaches.
no code implementations • 5 May 2021 • Chaoqi Yang, Cao Xiao, Lucas Glass, Jimeng Sun
Deep learning is revolutionizing predictive healthcare, including recommending medications to patients with complex health conditions.
1 code implementation • 11 May 2020 • Chaoqi Yang, Ruijie Wang, Shuochao Yao, Tarek Abdelzaher
Previous hypergraph expansions are solely carried out on either vertex level or hyperedge level, thereby missing the symmetric nature of data co-occurrence, and resulting in information loss.
1 code implementation • 30 Apr 2020 • Chaoqi Yang, Ruijie Wang, Fangwei Gao, Dachun Sun, Jiawei Tang, Tarek Abdelzaher
We further compare policies that rely on partial venue closure to policies that espouse wide-spread periodic testing instead (i. e., in lieu of social distancing).
Physics and Society Computers and Society Social and Information Networks
no code implementations • 30 Mar 2020 • Chaoqi Yang, Ruijie Wang, Shuochao Yao, Shengzhong Liu, Tarek Abdelzaher
Oversmoothing has been assumed to be the major cause of performance drop in deep graph convolutional networks (GCNs).
no code implementations • 18 Feb 2020 • Haolin Zhou, Chaoqi Yang, Xiaofeng Gao, Qiong Chen, Gongshen Liu, Guihai Chen
Online Real-Time Bidding (RTB) is a complex auction game among which advertisers struggle to bid for ad impressions when a user request occurs.
1 code implementation • 13 Feb 2020 • Chaoqi Yang, Jinyang Li, Ruijie Wang, Shuochao Yao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Tianshi Wang, Tarek F. Abdelzaher
In the synthetic dataset, our model reduces error by 40%.
no code implementations • 16 Nov 2019 • Kanika Narang, Chaoqi Yang, Adit Krishnan, Junting Wang, Hari Sundaram, Carolyn Sutter
We develop a novel induced relational graph convolutional network (IR-GCN) framework to address the question.