1 citations · 3 across the 14 of their papers we have counts for
4 papers · 1 filter
High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors
Elynn Chen, Yuefeng Han, Jiayu Li
Tensor classification is gaining importance across fields, yet handling partially observed data remains challenging. In this paper, we introduce a novel approach to tensor classifi…
TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting
Linghang Kong, Elynn Chen, Yuzhou Chen +1
Multi-dimensional time series data, such as matrix and tensor-variate time series, are increasingly prevalent in fields such as economics, finance, and climate science. Traditional…
High-Dimensional Tensor Classification with CP Low-Rank Discriminant Structure
Elynn Chen, Yuefeng Han, Jiayu Li
Tensor classification has become increasingly crucial in statistics and machine learning, with applications spanning neuroimaging, computer vision, and recommendation systems. Howe…
Factor Augmented Tensor-on-Tensor Neural Networks
Guanhao Zhou, Yuefeng Han, Xiufan Yu
This paper studies the prediction task of tensor-on-tensor regression in which both covariates and responses are multi-dimensional arrays (a.k.a., tensors) across time with arbitra…