40 citations · 42 across the 5 of their papers we have counts for
5 papers
SARMA: Scalable Low-Rank High-Dimensional Autoregressive Moving Averages via Tensor Decomposition
Feiqing Huang, Kexin Lu, Yao Zheng
Existing models for high-dimensional time series are overwhelmingly developed within the finite-order vector autoregressive (VAR) framework. However, the more flexible vector autor…
Supervised Factor Modeling for High-Dimensional Linear Time Series
Feiqing Huang, Kexin Lu, Guodong Li
Motivated by Tucker tensor decomposition, this paper imposes low-rank structures to the column and row spaces of coefficient matrices in a multivariate infinite-order vector autore…
A New Measure of Model Redundancy for Compressed Convolutional Neural Networks
Feiqing Huang, Yuefeng Si, Yao Zheng +1
While recently many designs have been proposed to improve the model efficiency of convolutional neural networks (CNNs) on a fixed resource budget, theoretical understanding of thes…
Do RNN and LSTM have Long Memory?
Jingyu Zhao, Feiqing Huang, Jia Lv +4
The LSTM network was proposed to overcome the difficulty in learning long-term dependence, and has made significant advancements in applications. With its success and drawbacks in…
Compact Autoregressive Network
Di Wang, Feiqing Huang, Jingyu Zhao +2
Autoregressive networks can achieve promising performance in many sequence modeling tasks with short-range dependence. However, when handling high-dimensional inputs and outputs, t…