5 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,…
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…