activity
20202023
most citedOnline Kernel CUSUM for Change-Point Detection

3 citations · 7 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG2023

Assessing Electricity Service Unfairness with Transfer Counterfactual Learning

Song Wei, Xiangrui Kong, Alinson Santos Xavier +3

Energy justice is a growing area of interest in interdisciplinary energy research. However, identifying systematic biases in the energy sector remains challenging due to confoundin…

cs.LG2023

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…

cs.LG2023

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…

cs.LG2023★ 1 cited

Causal Structural Learning from Time Series: A Convex Optimization Approach

Song Wei, Yao Xie

Structural learning, which aims to learn directed acyclic graphs (DAGs) from observational data, is foundational to causal reasoning and scientific discovery. Recent advancements f…

stat.ME2022★ 3 cited

Online Kernel CUSUM for Change-Point Detection

Song Wei, Yao Xie

We present a computationally efficient online kernel Cumulative Sum (CUSUM) method for change-point detection that utilizes the maximum over a set of kernel statistics to account f…

stat.ME2022

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

Song Wei, Chaofan Huang

We present a novel scheme to boost detection power for kernel maximum mean discrepancy based sequential change-point detection procedures. Our proposed scheme features an optimal s…

stat.AP2022

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

Song Wei, Yao Xie, Christopher S. Josef +1

Modern health care systems are conducting continuous, automated surveillance of the electronic medical record (EMR) to identify adverse events with increasing frequency; however, m…

cs.LG2021

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…

cs.LG2021★ 2 cited

Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization

Tianyi Liu, Yan Li, Song Wei +2

Numerous empirical evidences have corroborated the importance of noise in nonconvex optimization problems. The theory behind such empirical observations, however, is still largely…

math.ST2021★ 1 cited

Inferring serial correlation with dynamic backgrounds

Song Wei, Yao Xie, Dobromir Rahnev

Sequential data with serial correlation and an unknown, unstructured, and dynamic background is ubiquitous in neuroscience, psychology, and econometrics. Inferring serial correlati…

math.ST2020

Goodness-of-Fit Test for Mismatched Self-Exciting Processes

Song Wei, Shixiang Zhu, Minghe Zhang +1

Recently there have been many research efforts in developing generative models for self-exciting point processes, partly due to their broad applicability for real-world application…