Search Results for author: Chaoqi Yang

Found 15 papers, 10 papers with code

BIOT: Cross-data Biosignal Learning in the Wild

1 code implementation10 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.

EEG Seizure Detection

ManyDG: Many-domain Generalization for Healthcare Applications

1 code implementation21 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.

Domain Generalization Seizure Detection

GOCPT: Generalized Online Canonical Polyadic Tensor Factorization and Completion

1 code implementation8 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.

Self-supervised EEG Representation Learning for Automatic Sleep Staging

1 code implementation27 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.

EEG Electroencephalogram (EEG) +3

ATD: Augmenting CP Tensor Decomposition by Self Supervision

1 code implementation15 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.

Data Augmentation Dimensionality Reduction +3

MTC: Multiresolution Tensor Completion from Partial and Coarse Observations

1 code implementation14 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.

SafeDrug: Dual Molecular Graph Encoders for Recommending Effective and Safe Drug Combinations

no code implementations5 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.

Change Matters: Medication Change Prediction with Recurrent Residual Networks

no code implementations5 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.

Semi-supervised Hypergraph Node Classification on Hypergraph Line Expansion

1 code implementation11 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.

Classification Graph Learning +1

Analyzing the Design Space of Re-opening Policies and COVID-19 Outcomes in the US

1 code implementation30 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

Revisiting Over-smoothing in Deep GCNs

no code implementations30 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).

Node Classification

MoTiAC: Multi-Objective Actor-Critics for Real-Time Bidding

no code implementations18 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.

Reinforcement Learning (RL)

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