Cover Image

DANIEL: A Distributed and Scalable Approach for Global Representation Learning with EHR Applications

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Zebin, Gan, Ziming, Tang, Weijing, Xia, Zongqi, Cai, Tianrun, Cai, Tianxi, Lu, Junwei
Format:	Preprint
Published:	2025
Subjects:	Methodology Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Knowledge-Embedded Latent Projection for Robust Representation Learning
by: Tang, Weijing, et al.
Published: (2026)

Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data
by: Wang, Linshanshan, et al.
Published: (2025)

Latent Factor Point Processes for Patient Representation in Electronic Health Records
by: Knight, Parker, et al.
Published: (2025)

Inference of Dependency Knowledge Graph for Electronic Health Records
by: Xu, Zhiwei, et al.
Published: (2023)

Learning Sequential Decisions from Multiple Sources via Group-Robust Markov Decision Processes
by: Xu, Mingyuan, et al.
Published: (2026)

Representation-Enhanced Neural Knowledge Integration with Application to Large-Scale Medical Ontology Learning
by: Liu, Suqi, et al.
Published: (2024)

Federated Offline Reinforcement Learning
by: Zhou, Doudou, et al.
Published: (2022)

Confidence Diagram of Nonparametric Ranking for Uncertainty Assessment in Large Language Models Evaluation
by: Wang, Zebin, et al.
Published: (2024)

Integrated Analysis for Electronic Health Records with Structured and Sporadic Missingness
by: Tan, Jianbin, et al.
Published: (2025)

Transfer Learning with Distance Covariance for Random Forest: Error Bounds and an EHR Application
by: Li, Chenze, et al.
Published: (2025)

Minimax Regret Learning for Data with Heterogeneous Subgroups
by: Mo, Weibin, et al.
Published: (2024)

Contextual Online Uncertainty-Aware Preference Learning for Human Feedback
by: Lu, Nan, et al.
Published: (2025)

Towards Identifiability of Hierarchical Temporal Causal Representation Learning
by: Li, Zijian, et al.
Published: (2025)

Statistical Inference for Differentially Private Stochastic Gradient Descent
by: Xia, Xintao, et al.
Published: (2025)

First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint
by: Liu, Ziqi, et al.
Published: (2026)

Adversarial Drift-Aware Predictive Transfer: Toward Durable Clinical AI
by: Xiong, Xin, et al.
Published: (2026)

Nonparametric estimation of time-varying network connections by multi-stage smoothing
by: Lee, Jeonghwan, et al.
Published: (2026)

A Locally Adaptive Algorithm for Multiple Testing with Network Structure
by: Liang, Ziyi, et al.
Published: (2022)

Federated Learning of Quantile Inference under Local Differential Privacy
by: Cai, Leheng, et al.
Published: (2025)

Learning linear acyclic causal model including Gaussian noise using ancestral relationships
by: Cai, Ming, et al.
Published: (2024)

Representation-Aware Distributionally Robust Optimization: A Knowledge Transfer Framework
by: Wang, Zitao, et al.
Published: (2025)

Structure Maintained Representation Learning Neural Network for Causal Inference
by: Sun, Yang, et al.
Published: (2025)

Model-free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival
by: Wang, Xuan, et al.
Published: (2024)

Discrete Causal Representation Learning
by: Zhang, Wenjin, et al.
Published: (2026)

GRAND: Graph Release with Assured Node Differential Privacy
by: Liu, Suqing, et al.
Published: (2025)

Vector-Valued Distributional Reinforcement Learning Policy Evaluation: A Hilbert Space Embedding Approach
by: Mohammadi, Mehrdad, et al.
Published: (2026)

Contrastive Network Representation Learning
by: Dong, Zihan, et al.
Published: (2025)

Scalable Learning of Multivariate Distributions via Coresets
by: Ding, Zeyu, et al.
Published: (2026)

MixEHR-SurG: a joint proportional hazard and guided topic model for inferring mortality-associated topics from electronic health records
by: Li, Yixuan, et al.
Published: (2023)

Contrasting Global and Patient-Specific Regression Models via a Neural Network Representation
by: Behrens, Max, et al.
Published: (2026)

A Consistent and Scalable Algorithm for Best Subset Selection in Single Index Models
by: Tang, Borui, et al.
Published: (2023)

Knockoffs Inference under Privacy Constraints
by: Cai, Zhanrui, et al.
Published: (2025)

An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization
by: Hu, Shouri, et al.
Published: (2024)

Sampling-based federated inference for M-estimators with non-smooth objective functions
by: Li, Xiudi, et al.
Published: (2025)

Scalable Monte Carlo for Bayesian Learning
by: Fearnhead, Paul, et al.
Published: (2024)

Evaluation of Missing Data Analytical Techniques in Longitudinal Research: Traditional and Machine Learning Approaches
by: Tang, Dandan, et al.
Published: (2024)

Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
by: Wang, Zhenyu, et al.
Published: (2023)

Causal Effect Estimation with Learned Instrument Representations
by: Dean, Frances, et al.
Published: (2026)

Representation Retrieval Learning for Heterogeneous Data Integration
by: Xu, Qi, et al.
Published: (2025)

MMDCP: A Distribution-free Approach to Outlier Detection and Classification with Coverage Guarantees and SCW-FDR Control
by: Lin, Youwu, et al.
Published: (2025)