105 citations · 372 across the 39 of their papers we have counts for
9 papers · 1 filter
A Convergent ADMM Framework for Efficient Neural Network Training
Junxiang Wang, Hongyi Li, Liang Zhao
As a well-known optimization framework, the Alternating Direction Method of Multipliers (ADMM) has achieved tremendous success in many classification and regression applications. R…
KNAS: Green Neural Architecture Search
Jingjing Xu, Liang Zhao, Junyang Lin +3
Many existing neural architecture search (NAS) solutions rely on downstream training for architecture evaluation, which takes enormous computations. Considering that these computat…
Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling
Liang Zhao, Wei Li, Ruihan Bao +3
Trading volume movement prediction is the key in a variety of financial applications. Despite its importance, there is few research on this topic because of its requirement for com…
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Zhiqian Chen, Fanglan Chen, Lei Zhang +7
Deep learning's performance has been extensively recognized recently. Graph neural networks (GNNs) are designed to deal with graph-structural data that classical deep learning does…
Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning
Yuyang Gao, Giorgio A. Ascoli, Liang Zhao
Continual learning is considered a promising step towards next-generation Artificial Intelligence (AI), where deep neural networks (DNNs) make decisions by continuously learning a…
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition
Boxiang Dong, Aparna S. Varde, Danilo Stevanovic +2
Handwriting recognition is of crucial importance to both Human Computer Interaction (HCI) and paperwork digitization. In the general field of Optical Character Recognition (OCR), h…
Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss
Boxiang Dong, Hui, Wang +5
Cyber attacks pose crucial threats to computer system security, and put digital treasuries at excessive risks. This leads to an urgent call for an effective intrusion detection sys…
Sign-regularized Multi-task Learning
Johnny Torres, Guangji Bai, Junxiang Wang +3
Multi-task learning is a framework that enforces different learning tasks to share their knowledge to improve their generalization performance. It is a hot and active domain that s…
GP: Context-free Grammar Pre-training for Text-to-SQL Parsers
Liang Zhao, Hexin Cao, Yunsong Zhao
A new method for Text-to-SQL parsing, Grammar Pre-training (GP), is proposed to decode deep relations between question and database. Firstly, to better utilize the information of d…