activity
20172023
most citedLess Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

89 citations · 264 across the 31 of their papers we have counts for

collaborators

31 papers

cs.LG2023

Developing A Fair Individualized Polysocial Risk Score (iPsRS) for Identifying Increased Social Risk of Hospitalizations in Patients with Type 2 Diabetes (T2D)

Yu Huang, Jingchuan Guo, William T Donahoo +7

Background: Racial and ethnic minority groups and individuals facing social disadvantages, which often stem from their social determinants of health (SDoH), bear a disproportionate…

stat.AP2023★ 1 cited

The impact of electronic health records (EHR) data continuity on prediction model fairness and racial-ethnic disparities

Yu Huang, Jingchuan Guo, Zhaoyi Chen +6

Electronic health records (EHR) data have considerable variability in data completeness across sites and patients. Lack of "EHR data-continuity" or "EHR data-discontinuity", define…

cs.CL2023★ 2 cited

Improving Primary Healthcare Workflow Using Extreme Summarization of Scientific Literature Based on Generative AI

Gregor Stiglic, Leon Kopitar, Lucija Gosak +5

Primary care professionals struggle to keep up to date with the latest scientific literature critical in guiding evidence-based practice related to their daily work. To help solve…

cs.AI2023★ 8 cited

Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance

Yuchen Fang, Zhenggang Tang, Kan Ren +7

Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance…

cs.LG2023★ 42 cited

Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series

Jiawen Zhang, Shun Zheng, Wei Cao +2

Irregularly sampled multivariate time series are ubiquitous in various fields, particularly in healthcare, and exhibit two key characteristics: intra-series irregularity and inter-…

cs.LG2023

UADB: Unsupervised Anomaly Detection Booster

Hangting Ye, Zhining Liu, Xinyi Shen +6

Unsupervised Anomaly Detection (UAD) is a key data mining problem owing to its wide real-world applications. Due to the complete absence of supervision signals, UAD methods rely on…