1 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
High-Dimensional Tensor Discriminant Analysis: Low-Rank Discriminant Structure, Representation Synergy, and Theoretical Guarantees
Elynn Chen, Yuefeng Han, Jiayu Li
High-dimensional tensor-valued predictors arise in modern applications, increasingly as learned representations from neural networks. Existing tensor classification methods rely on…
Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control
Lingchong Liu, Elynn Chen, Yuefeng Han +1
Biochemical discovery increasingly relies on classifying molecular structures when the consequences of different errors are highly asymmetric. In mutagenicity and carcinogenicity,…
Modewise Additive Factor Model for Matrix Time Series
Elynn Chen, Yuefeng Han, Jiayu Li +1
We introduce a Modewise Additive Factor Model (MAFM) for matrix-valued time series that captures row-specific and column-specific latent effects through an additive structure, offe…
Time-Varying Factor-Augmented Models for Volatility Forecasting
Duo Zhang, Jiayu Li, Junyi Mo +1
Accurate volatility forecasts are vital in modern finance for risk management, portfolio allocation, and strategic decision-making. However, existing methods face key limitations.…
ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation
Junyi Mo, Jiayu Li, Duo Zhang +1
Missing data in financial panels presents a critical obstacle, undermining asset-pricing models and reducing the effectiveness of investment strategies. Such panels are often inher…
Statistical Inference for Low-Rank Tensor Models
Ke Xu, Elynn Chen, Yuefeng Han
Statistical inference for tensors has emerged as a critical challenge in analyzing high-dimensional data in modern data science. This paper introduces a unified framework for infer…