10 citations · 21 across the 10 of their papers we have counts for
6 papers · 1 filter
Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer
Jiaying Lu, Stephanie R. Brown, Songyuan Liu +8
Early prediction of pediatric cardiac arrest (CA) is critical for timely intervention in high-risk intensive care settings. We introduce PedCA-FT, a novel transformer-based framewo…
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling
Shifan Zhao, Jiaying Lu, Ji Yang +2
Gaussian Process Regression (GPR) is widely used in statistics and machine learning for prediction tasks requiring uncertainty measures. Its efficacy depends on the appropriate spe…
MedDiff: Generating Electronic Health Records using Accelerated Denoising Diffusion Model
Huan He, Shifan Zhao, Yuanzhe Xi +1
Due to patient privacy protection concerns, machine learning research in healthcare has been undeniably slower and limited than in other application domains. High-quality, realisti…
MuG: A Multimodal Classification Benchmark on Game Data with Tabular, Textual, and Visual Fields
Jiaying Lu, Yongchen Qian, Shifan Zhao +2
Previous research has demonstrated the advantages of integrating data from multiple sources over traditional unimodal data, leading to the emergence of numerous novel multimodal ap…
An Efficient Nonlinear Acceleration method that Exploits Symmetry of the Hessian
Huan He, Shifan Zhao, Ziyuan Tang +3
Nonlinear acceleration methods are powerful techniques to speed up fixed-point iterations. However, many acceleration methods require storing a large number of previous iterates an…
GDA-AM: On the effectiveness of solving minimax optimization via Anderson Acceleration
Huan He, Shifan Zhao, Yuanzhe Xi +2
Many modern machine learning algorithms such as generative adversarial networks (GANs) and adversarial training can be formulated as minimax optimization. Gradient descent ascent (…