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Found 8 papers, 0 papers with code
Generalization and Risk Bounds for Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have achieved great success in the prediction of sequential data.
Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information
This paper investigates statistical inference for noisy matrix completion in a semi-supervised model when auxiliary covariates are available.
A New Causal Rule Learning Approach to Interpretable Estimation of Heterogeneous Treatment Effect
Interpretability plays a critical role in the application of statistical learning for estimating heterogeneous treatment effects (HTE) for complex diseases.
SleepEGAN: A GAN-enhanced Ensemble Deep Learning Model for Imbalanced Classification of Sleep Stages
Deep neural networks have played an important role in automatic sleep stage classification because of their strong representation and in-model feature transformation abilities.
Privacy-Preserving Community Detection for Locally Distributed Multiple Networks
To remove the bias incurred by RR and the squared network matrices, we develop a two-step bias-adjustment procedure.
Causal Inference of General Treatment Effects using Neural Networks with A Diverging Number of Confounders
This paper considers a generalized optimization framework for efficient estimation of general treatment effects using artificial neural networks (ANNs) to approximate the unknown nuisance function of growing-dimensional confounders.
Detecting Latent Communities in Network Formation Models
This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed effects.
Multivariate Functional Regression via Nested Reduced-Rank Regularization
We propose a nested reduced-rank regression (NRRR) approach in fitting regression model with multivariate functional responses and predictors, to achieve tailored dimension reduction and facilitate interpretation/visualization of the resulting functional model.
