5 papers
Blurring Mean Shift for Clustering Functional Data: A Scalable Algorithm and Convergence Analysis
Toshinari Morimoto, Ting-Li Chen, Su-Yun Huang +1
This paper extends the blurring mean shift algorithm from vector-valued data to functional data, enabling effective clustering in infinite-dimensional settings without requiring sp…
Forward Regression via Gram-Schmidt Orthogonalization for Ultra-High Dimensional Linear Models
Jialuo Chen, Zhaoxing Gao, Yifan Jiang +1
Forward regression is a classical and effective tool for variable screening in ultra-high dimensional linear models, but its standard projection-based implementation can be computa…
High-Dimensional Spatial Arbitrage Pricing Theory with Heterogeneous Interactions
Zhaoxing Gao, Sihan Tu, Ruey S. Tsay
This paper investigates estimation and inference of a Spatial Arbitrage Pricing Theory (SAPT) model that integrates spatial interactions with multi-factor analysis, accommodating b…
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection
Paul Boniol, Ashwin K. Krishna, Marine Bruel +7
Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications. In contrast to other domains…
Modeling High-Dimensional Dependent Data in the Presence of Many Explanatory Variables and Weak Signals
Zhaoxing Gao, Ruey S. Tsay
This article considers a novel and widely applicable approach to modeling high-dimensional dependent data when a large number of explanatory variables are available and the signal-…