b'Yao Xie'

research

∙ 08/10/2023

From CNN to Transformer: A Review of Medical Image Segmentation Models

Medical image segmentation is an important step in medical image analysi...

0 Wenjian Yao, et al. ∙

research

∙ 07/15/2023

A Graph-Prediction-Based Approach for Debiasing Underreported Data

We present a novel Graph-based debiasing Algorithm for Underreported Dat...

0 Hanyang Jiang, et al. ∙

research

∙ 06/20/2023

Deep graph kernel point processes

Point process models are widely used to analyze asynchronous events occu...

0 Zheng Dong, et al. ∙

research

∙ 05/16/2023

Transfer Causal Learning: Causal Effect Estimation with Knowledge Transfer

A novel problem of improving causal effect estimation accuracy with the ...

0 Song Wei, et al. ∙

research

∙ 02/15/2023

Variable Selection for Kernel Two-Sample Tests

We consider the variable selection problem for two-sample tests, aiming ...

3 Jie Wang, et al. ∙

research

∙ 01/26/2023

Causal Structural Learning from Time Series: A Convex Optimization Approach

Structural learning, which aims to learn directed acyclic graphs (DAGs) ...

0 Song Wei, et al. ∙

research

∙ 01/26/2023

Causal Graph Discovery from Self and Mutually Exciting Time Series

We present a generalized linear structural causal model, coupled with a ...

0 Song Wei, et al. ∙

research

∙ 11/29/2022

Novelty Detection for Election Fraud: A Case Study with Agent-Based Simulation Data

In this paper, we propose a robust election simulation model and indepen...

0 Khurram Yamin, et al. ∙

research

∙ 11/28/2022

Online Kernel CUSUM for Change-Point Detection

We develop an online kernel Cumulative Sum (CUSUM) procedure, which cons...

0 Song Wei, et al. ∙

research

∙ 11/22/2022

Online Detection Of Supply Chain Network Disruptions Using Sequential Change-Point Detection for Hawkes Processes

In this paper, we attempt to detect an inflection or change-point result...

0 Khurram Yamin, et al. ∙

research

∙ 11/21/2022

Spatio-temporal point processes with deep non-stationary kernels

Point process data are becoming ubiquitous in modern applications, such ...

0 Zheng Dong, et al. ∙

research

∙ 11/14/2022

Tides Need STEMMED: A Locally Operating Spatio-Temporal Mutually Exciting Point Process with Dynamic Network for Improving Opioid Overdose Death Prediction

We develop a Spatio-TEMporal Mutually Exciting point process with Dynami...

0 Che-Yi Liao, et al. ∙

research

∙ 10/31/2022

Training Neural Networks for Sequential Change-point Detection

Detecting an abrupt distributional shift of the data stream, known as ch...

0 Junghwan Lee, et al. ∙

research

∙ 10/31/2022

Data-Adaptive Symmetric CUSUM for Sequential Change Detection

Detecting change points sequentially in a streaming setting, especially ...

0 Nauman Ahad, et al. ∙

research

∙ 10/26/2022

Optimal Sub-sampling to Boost Power of Kernel Sequential Change-point Detection

We present a novel scheme to boost detection power for kernel maximum me...

0 Song Wei, et al. ∙

research

∙ 10/24/2022

Online Critical-State Detection of Sepsis Among ICU Patients using Jensen-Shannon Divergence

Sepsis is a severe medical condition caused by a dysregulated host respo...

0 Jeffrey R. Smith, et al. ∙

research

∙ 10/11/2022

Sequential change-point detection: Computation versus statistical performance

Change-point detection studies the problem of detecting the changes in t...

0 Haoyun Wang, et al. ∙

research

∙ 09/09/2022

Granger Causal Chain Discovery for Sepsis-Associated Derangements via Multivariate Hawkes Processes

Modern health care systems are conducting continuous, automated surveill...

0 Song Wei, et al. ∙

research

∙ 07/07/2022

Neural Stein critics with staged L^2-regularization

Learning to differentiate model distributions from observed data is a fu...

0 Matthew Repasky, et al. ∙

research

∙ 06/14/2022

Window-Limited CUSUM for Sequential Change Detection

We study the parametric online changepoint detection problem, where the ...

0 Liyan Xie, et al. ∙

research

∙ 06/02/2022

Invertible Neural Networks for Graph Prediction

In this work, we address conditional generation using deep invertible ne...

82 Chen Xu, et al. ∙

research

∙ 05/04/2022

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks

Two-sample tests are important areas aiming to determine whether two col...

1 Jie Wang, et al. ∙

research

∙ 03/08/2022

PERCEPT: a new online change-point detection method using topological data analysis

Topological data analysis (TDA) provides a set of data analysis tools fo...

0 Xiaojun Zheng, et al. ∙

research

∙ 02/17/2022

Training neural networks using monotone variational inequality

Despite the vast empirical success of neural networks, theoretical under...

0 Xiuyuan Cheng, et al. ∙

research

∙ 02/09/2022

A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets

Hypothesis testing for small-sample scenarios is a practically important...

11 Jie Wang, et al. ∙

research

∙ 02/08/2022

Police Text Analysis: Topic Modeling and Spatial Relative Density Estimation

We analyze a large corpus of police incident narrative documents in unde...

24 Sarah Huestis-Mitchell, et al. ∙

research

∙ 02/08/2022

Learning Sinkhorn divergences for supervised change point detection

Many modern applications require detecting change points in complex sequ...

0 Nauman Ahad, et al. ∙

research

∙ 09/24/2021

Sinkhorn Distributionally Robust Optimization

We study distributionally robust optimization with Sinkorn distance – a ...

0 Jie Wang, et al. ∙

research

∙ 09/20/2021

A spatio-temporal analysis for power grid resilience to extreme weather

In recent years, extreme weather events frequently cause large-scale pow...

0 Shixiang Zhu, et al. ∙

research

∙ 09/18/2021

Non-stationary spatio-temporal point process modeling for high-resolution COVID-19 data

Most COVID-19 studies commonly report figures of the overall infection a...

0 Zheng Dong, et al. ∙

research

∙ 08/30/2021

Multi-Resolution Spatio-Temporal Prediction with Application to Wind Power Generation

This paper proposes a spatio-temporal model for wind speed prediction wh...

0 Shixiang Zhu, et al. ∙

research

∙ 08/29/2021

Survival Analysis with Graph-Based Regularization for Predictors

We study the variable selection problem in survival analysis to identify...

0 Xi He, et al. ∙

research

∙ 06/20/2021

Neural Spectral Marked Point Processes

Self- and mutually-exciting point processes are popular models in machin...

0 Shixiang Zhu, et al. ∙

research

∙ 06/06/2021

Neural Tangent Kernel Maximum Mean Discrepancy

We present a novel neural network Maximum Mean Discrepancy (MMD) statist...

0 Xiuyuan Cheng, et al. ∙

research

∙ 06/04/2021

Inferring Granger Causality from Irregularly Sampled Time Series

Continuous, automated surveillance systems that incorporate machine lear...

0 Song Wei, et al. ∙

research

∙ 05/31/2021

Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data

Recently, the Centers for Disease Control and Prevention (CDC) has worke...

26 Shixiang Zhu, et al. ∙

research

∙ 05/29/2021

Robust Hypothesis Testing with Wasserstein Uncertainty Sets

We consider a data-driven robust hypothesis test where the optimal test ...

0 Liyan Xie, et al. ∙

research

∙ 05/25/2021

Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data

We develop a distribution-free, unsupervised anomaly detection method ca...

0 Yao Xie, et al. ∙

research

∙ 05/07/2021

Kernel MMD Two-Sample Tests for Manifold Data

We present a study of kernel MMD two-sample test statistics in the manif...

0 Xiuyuan Cheng, et al. ∙

research

∙ 04/18/2021

Harvesting data revolution for transmission electron microscopy (TEM) using signal processing

TEM (Transmission Electron Microscopy) is a powerful tool for imaging ma...

0 Shixiang Zhu, et al. ∙

research

∙ 04/09/2021

Sequential (Quickest) Change Detection: Classical Results and New Directions

Online detection of changes in stochastic systems, referred to as sequen...

0 Liyan Xie, et al. ∙

research

∙ 03/30/2021

Data-Driven Optimization for Police Zone Design

We present a data-driven optimization framework for redesigning police p...

0 Shixiang Zhu, et al. ∙

research

∙ 02/27/2021

Online High-Dimensional Change-Point Detection using Topological Data Analysis

Topological Data Analysis (TDA) is a rapidly growing field, which studie...

0 Xiaojun Zheng, et al. ∙

research

∙ 02/12/2021

Two-sample Test with Kernel Projected Wasserstein Distance

We develop a kernel projected Wasserstein distance for the two-sample te...

0 Jie Wang, et al. ∙

research

∙ 02/11/2021

Optimality of Graph Scanning Statistic for Online Community Detection

Sequential change-point detection for graphs is a fundamental problem fo...

0 Liyan Xie, et al. ∙

research

∙ 02/10/2021

Sequential change-point detection for mutually exciting point processes over networks

We present a new CUSUM procedure for sequentially detecting change-point...

0 Haoyun Wang, et al. ∙

research

∙ 02/09/2021

Balanced Districting on Grid Graphs with Provable Compactness and Contiguity

Given a graph G = (V,E) with vertex weights w(v) and a desired number of...

0 Cyrus Hettle, et al. ∙

research

∙ 01/27/2021

Solar Radiation Anomaly Events Modeling Using Spatial-Temporal Mutually Interactive Processes

Modeling and predicting solar events, in particular, the solar ramping e...

0 Minghe Zhang, et al. ∙

research

∙ 01/26/2021

Inferring serial correlation with dynamic backgrounds

Sequential data with serial correlation and an unknown, unstructured, an...

0 Song Wei, et al. ∙

research

∙ 01/05/2021

Bayesian Uncertainty Quantification for Low-rank Matrix Completion

We consider the problem of uncertainty quantification for an unknown low...

0 Henry Shaowu Yuchi, et al. ∙

Yao Xie

Featured Co-authors