7 citations · 15 across the 6 of their papers we have counts for
6 papers
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation
Kan Chen, Qishuo Yin, Qi Long
Estimating treatment effects is of great importance for many biomedical applications with observational data. Particularly, interpretability of the treatment effects is preferable…
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability
Qiyiwen Zhang, Zhiqi Bu, Kan Chen +1
Bayesian neural network (BNN) allows for uncertainty quantification in prediction, offering an advantage over regular neural networks that has not been explored in the differential…
Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing Algorithm
Kan Chen, Zhiqi Bu, Shiyun Xu
Sparse Group LASSO (SGL) is a regularized model for high-dimensional linear regression problems with grouped covariates. SGL applies and penalties on the individual pre…
Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies
Kan Chen, Siyu Heng, Qi Long +1
One central goal of design of observational studies is to embed non-experimental data into an approximate randomized controlled trial using statistical matching. Despite empirical…
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
Zhiqi Bu, Shiyun Xu, Kan Chen
When equipped with efficient optimization algorithms, the over-parameterized neural networks have demonstrated high level of performance even though the loss function is non-convex…
A general learning algorithm for solving optimization problems and its application to the spin glass problem
Kan Chen
We propose a general learning algorithm for solving optimization problems, based on a simple strategy of trial and adaptation. The algorithm maintains a probability distribution of…