12 citations · 19 across the 11 of their papers we have counts for
12 papers
A Graph-Prediction-Based Approach for Debiasing Underreported Data
Hanyang Jiang, Yao Xie
We present a novel Graph-based debiasing Algorithm for Underreported Data (GRAUD) aiming at an efficient joint estimation of event counts and discovery probabilities across spatial…
Transfer Learning for Causal Effect Estimation
Song Wei, Hanyu Zhang, Ronald Moore +2
We present a Transfer Causal Learning (TCL) framework when target and source domains share the same covariate/feature spaces, aiming to improve causal effect estimation accuracy in…
Generalized generalized linear models: Convex estimation and online bounds
Anatoli Juditsky, Arkadi Nemirovski, Yao Xie +1
We introduce a new computational framework for estimating parameters in generalized generalized linear models (GGLM), a class of models that extends the popular generalized linear…
Causal Graph Discovery from Self and Mutually Exciting Time Series
Song Wei, Yao Xie, Christopher S. Josef +1
We present a generalized linear structural causal model, coupled with a novel data-adaptive linear regularization, to recover causal directed acyclic graphs (DAGs) from time series…
Sequential Predictive Conformal Inference for Time Series
Chen Xu, Yao Xie
We present a new distribution-free conformal prediction algorithm for sequential data (e.g., time series), called the \textit{sequential predictive conformal inference} (\texttt{SP…
Spatio-Temporal Wildfire Prediction using Multi-Modal Data
Chen Xu, Yao Xie, Daniel A. Zuniga Vazquez +2
Due to severe societal and environmental impacts, wildfire prediction using multi-modal sensing data has become a highly sought-after data-analytical tool by various stakeholders (…
Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge
Jingge Wang, Liyan Xie, Yao Xie +2
Domain generalization aims at learning a universal model that performs well on unseen target domains, incorporating knowledge from multiple source domains. In this research, we con…
Conformal prediction set for time-series
Chen Xu, Yao Xie
When building either prediction intervals for regression (with real-valued response) or prediction sets for classification (with categorical responses), uncertainty quantification…
A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets
Jie Wang, Yao Xie
Hypothesis testing for small-sample scenarios is a practically important problem. In this paper, we investigate the robust hypothesis testing problem in a data-driven manner, where…
Survival Analysis with Graph-Based Regularization for Predictors
Liyan Xie, Xi He, Pinar Keskinocak +1
We study the variable selection problem in survival analysis to identify the most important factors affecting survival time. Our method incorporates prior knowledge of mutual corre…
Causal Graph Discovery from Self and Mutually Exciting Time Series
Song Wei, Yao Xie, Christopher S. Josef +1
We present a generalized linear structural causal model, coupled with a novel data-adaptive linear regularization, to recover causal directed acyclic graphs (DAGs) from time series…
Conformal prediction for time series
Chen Xu, Yao Xie
We develop a general framework for constructing distribution-free prediction intervals for time series. Theoretically, we establish explicit bounds on conditional and marginal cove…