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Neuroevolutionary Feature Representations for Causal Inference
Within the field of causal inference, we consider the problem of estimating heterogeneous treatment effects from data. We propose and validate a...
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An HPC hybrid parallel approach to the experimental analysis of Fermat’s theorem extension to arbitrary dimensions on heterogeneous computer systems
In this work, we consider the empirical, computational, study of the generalized Fermat’s last theorem conjecture recently proposed using Minkowski...
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Rapid facial expression recognition under part occlusion based on symmetric SURF and heterogeneous soft partition network
Recently, deep learning has made great achievements in facial expression recognition. However, occlusion and large skew will greatly affect the...
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Coarsening effects on k-partite network classification
The growing data size poses challenges for storage and computational processing time in semi-supervised models, making their practical application...
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Ensemble Learning with Time Accumulative Effect for Early Diagnosis of Alzheimer’s Disease
Alzheimer’s disease (AD) is a neurodegenerative disorder. Early diagnosis of AD is critical for disease management and treatment options to slow...
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Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
Causal Impact (CI) measurement is broadly used across the industry to inform both short- and long-term investment decisions of various types. In this...
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What Can the Millions of Random Treatments in Nonexperimental Data Reveal About Causes?
We propose a new method to estimate causal effects from nonexperimental data. Each pair of sample units is first associated with a stochastic...
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Machine learning-based ABA treatment recommendation and personalization for autism spectrum disorder: an exploratory study
Autism spectrum is a brain development condition that impairs an individual’s capacity to communicate socially and manifests through strict routines...
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Auxiliary diagnosis of heterogeneous data of Parkinson’s disease based on improved convolution neural network
Parkinson’s disease (PD) is a kind of nervous system degenerative disease frequently occurring in the elderly over sixty years old. With the...
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Unmasking academic cheating behavior in the artificial intelligence era: Evidence from Vietnamese undergraduates
The proliferation of artificial intelligence (AI) technology has brought both innovative opportunities and unprecedented challenges to the education...
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Regularization for Uplift Regression
We address the problem of regularization of linear regression models in uplift modeling and heterogeneous treatment effect estimation. We consider...
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Efficiency and productivity for decision making on low-power heterogeneous CPU+GPU SoCs
Markov decision processes provide a formal framework for a computer to make decisions autonomously and intelligently when the effects of its actions...
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Digitally Controlled Light, Sound and Aroma Therapy
Light, sound and aroma therapy are often used as complementary medical methods in the treatment of people with neuropsychiatric symptoms. However,...
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Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models
Image-based precision medicine aims to personalize treatment decisions based on an individual’s unique imaging features so as to improve their...
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Survival Hierarchical Agglomerative Clustering: A Semi-Supervised Clustering Method Incorporating Survival Data
Heterogeneity in patient populations presents a significant challenge for healthcare professionals, as different sub-populations may require...
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An improved text classification modelling approach to identify security messages in heterogeneous projects
Security remains under-addressed in many organisations, illustrated by the number of large-scale software security breaches. Preventing breaches can...
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Mobile English Learning: A Meta-analysis
The advantages of mobile learning (m-learning) in English education have been widely described in previous research; however, there is little...
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Achieving Seamless Semantic Interoperability and Enhancing Text Embedding in Healthcare IoT: A Deep Learning Approach with Survey
Achieving semantic interoperability in healthcare is one of the significant challenges in the rapidly expanding healthcare sector. On the other hand,...
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KGCN-DDA: A Knowledge Graph Based GCN Method for Drug-Disease Association Prediction
Exploring the potential efficacy of a drug is a valid approach for drug discovery with shorter development times and lower costs. Recently, several...
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Continuous treatment effect estimation via generative adversarial de-confounding
One fundamental problem in causal inference is the treatment effect estimation in observational studies, and its key challenge is to handle the...
