2 citations · 5 across the 9 of their papers we have counts for
11 papers
Quickest Change-point Detection in Generalized Linear Models with Variational Estimation
Jonghyeok Lee, Yao Xie
We consider quickest change-point detection in generalized linear models when the post-change parameter is unknown. Such problems arise, for example, when monitoring whether the re…
Conformal Prediction for Time Series with Deep Sequence Models
Junghwan Lee, Jonghyeok Lee, Yao Xie
Recent advances in deep learning for time series prediction have amplified the need for reliable uncertainty quantification. Conformal prediction has gained attention as a distribu…
Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series
Hanyang Jiang, Rina Foygel Barber, Ashwin Pananjady +1
Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable and is treated symmetrically during training…
Efficient First-Order Methods for Estimating Generalized Additive Index Models
Ziyu Peng, Linglingzhi Zhu, Yao Xie
Generalized additive index models (GAIMs) offer a flexible semiparametric framework for capturing complex data relationships, balancing the interpretability of parametric models wi…
Flow-based Conformal Prediction for Multi-dimensional Time Series
Junghwan Lee, Chen Xu, Yao Xie
Time series prediction underpins a broad range of downstream tasks across many scientific domains. Recent advances and increasing adoption of black-box machine learning models for…
Spatial Conformal Inference through Localized Quantile Regression
Hanyang Jiang, Yao Xie
Reliable uncertainty quantification at unobserved spatial locations, especially in the presence of complex and heterogeneous datasets, remains a core challenge in spatial statistic…
Transformer Conformal Prediction for Time Series
Junghwan Lee, Chen Xu, Yao Xie
We present a conformal prediction method for time series using the Transformer architecture to capture long-memory and long-range dependencies. Specifically, we use the Transformer…
Learning Cellular Network Connection Quality with Conformal
Hanyang Jiang, Elizabeth Belding, Ellen Zegure +1
In this paper, we address the problem of uncertainty quantification for cellular network speed. It is a well-known fact that the actual internet speed experienced by a mobile phone…
Kernel-based Optimally Weighted Conformal Time-Series Prediction
Jonghyeok Lee, Chen Xu, Yao Xie
In this work, we present a novel conformal prediction method for time-series, which we call Kernel-based Optimally Weighted Conformal Prediction Intervals (KOWCPI). Specifically, K…
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Chen Xu, Hanyang Jiang, Yao Xie
Conformal prediction (CP) has been a popular method for uncertainty quantification because it is distribution-free, model-agnostic, and theoretically sound. For forecasting problem…
Mobile Internet Quality Estimation using Self-Tuning Kernel Regression
Hanyang Jiang, Henry Shaowu Yuchi, Elizabeth Belding +2
Modeling and estimation for spatial data are ubiquitous in real life, frequently appearing in weather forecasting, pollution detection, and agriculture. Spatial data analysis often…