15 citations · 28 across the 26 of their papers we have counts for
8 papers · 1 filter
Structured Adaptive Tensor Prediction for Streaming Data
Zhen Qin, Yang Chen
Matrix-valued time series arise in a wide range of applications, such as spatio-temporal data from medical imaging and geophysics. Existing methods are mainly designed for static s…
Learning to Adapt: In-Context Learning Beyond Stationarity
Zhen Qin, Jiachen Jiang, Zhihui Zhu
Transformer models have become foundational across a wide range of scientific and engineering domains due to their strong empirical performance. A key capability underlying their s…
In-Context Learning for Non-Stationary MIMO Equalization
Jiachen Jiang, Zhen Qin, Zhihui Zhu
Channel equalization is fundamental for mitigating distortions such as frequency-selective fading and inter-symbol interference. Unlike standard supervised learning approaches that…
A Scalable Factorization Approach for High-Order Structured Tensor Recovery
Zhen Qin, Michael B. Wakin, Zhihui Zhu
Tensor decompositions, which represent an -order tensor using approximately factors of much smaller dimensions, can significantly reduce the number of parameters. This is pa…
On the Convergence of Gradient Descent on Learning Transformers with Residual Connections
Zhen Qin, Jinxin Zhou, Jiachen Jiang +1
Transformer models have emerged as fundamental tools across various scientific and engineering disciplines, owing to their outstanding performance in diverse applications. Despite…
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition
Zhen Qin, Zhihui Zhu
Recently, a tensor-on-tensor (ToT) regression model has been proposed to generalize tensor recovery, encompassing scenarios like scalar-on-tensor regression and tensor-on-vector re…