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Stochastic coordination in heterogeneous load balancing systems
Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically...
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Modeling Treatment Effect with Cross-Domain Data
Treatment effect estimation has received increasing attention recently. However, the issue of data sparsity often poses a significant challenge,...
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DP-MHAN: A Disease Prediction Method Based on Metapath Aggregated Heterogeneous Graph Attention Networks
Disease prediction as an important component of medical assistant diagnostic systems has received much attention from researchers. Many studies...
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Treatment Effect Estimation Under Unknown Interference
Causal inference is a powerful tool for effective decision-making in various areas, such as medicine and commerce. For example, it allows businesses...
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MulEA: Multi-type Entity Alignment of Heterogeneous Medical Knowledge Graphs
The large-scale application of medical knowledge graphs has greatly raised the intelligence level of modern medicine. Considering that entity...
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Investigating effects of teachers in flipped classroom: a randomized controlled trial study of classroom level heterogeneity
The increased popularity of flipped classroom in higher education warrants more thorough investigation of the pedagogical format’s effects on student...
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Promising Long Term Effects of ASSISTments Online Math Homework Support
Math performance continues to be an important focus for improvement. Many districts adopted educational technology programs to support student...
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Detecting Medical Insurance Fraud Using a Heterogeneous Information Network with a Multi-behavior Pattern
Medical insurance frauds impose huge losses on the medical insurance funds. Hence, efficient detection of medical insurance frauds is essential for...
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Tracking treatment effect heterogeneity in evolving environments
Heterogeneous treatment effect (HTE) estimation plays a crucial role in develo** personalized treatment plans across various applications....
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A Minimal Model of Cancer Growth, Metastasis and Treatment
The paper is concerned with modeling cancer growth, metastasis and response to anticancer treatment in a heterogeneous population of patients....
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An Improved Neural Network Model for Treatment Effect Estimation
Nowadays, in many scientific and industrial fields there is an increasing need for estimating treatment effects and answering causal questions. The...
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The SPECTRA Project: Biomedical Data for Supporting the Detection of Treatment Resistant Schizophrenia
The SPECTRA project aims at supporting the clinician in the detection of patients suffering from a specific subclass of Schizophrenia (SZ),...
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Towards dynamic and heterogeneous social IoT environments
Nowadays, there are millions of smart devices connected to the Internet. The purpose of these devices is to make people’s lives easier. Thanks to the...
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Global and Individual Treatment Effects Using Machine Learning Methods
Identifying students at risk of failing a course has potential benefits, such as recommending the At-Risk students to various interventions that...
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Heterogeneous Institutional Shareholding, Internal Control and Corporate Social Responsibility: Evidence from Chinese Listed Companies
The study analyzes the impact of heterogeneous institutional shareholding on corporate social responsibility (CSR) performance and corporate internal...
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HIFINet: Examination-Diagnosis-Treatment Hierarchical Feedback Interaction Network for Medication Recommendation
Medication combination recommendation is critical in clinic, since accurately predicting therapeutic drug can provide essential decision support to...
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Heterogeneous Computing Systems in Problems of Modeling Filaments Formation and Pre-stellar Objects
Modeling of astrophysical processes requires the use of modern means of supporting labor-intensive calculations with more efficient parallelization...
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Tasks Scheduling Through Hybrid Genetic Algorithm in Real-Time System on Heterogeneous Environment
The tasks scheduling issue on parallel processors in real-time system is part of the NP-hard issues. This manuscript developed a model for solving...
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Causal Inference with Heterogeneous Confounding Data: A Penalty Approach
Causal inference directly explores the causality among variables, in which average causal effect estimation is a fundamental task. But for...
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A comparative study of policy shock response effects based on the data algorithm of the DSGE model
The degree to which the banking sector opens up will immediately impact the structure of the national financial system, which will then directly...
