48 citations · 135 across the 9 of their papers we have counts for
9 papers
Sequential Subset Matching for Dataset Distillation
Jiawei Du, Qin Shi, Joey Tianyi Zhou
Dataset distillation is a newly emerging task that synthesizes a small-size dataset used in training deep neural networks (DNNs) for reducing data storage and model training costs.…
Spanning Training Progress: Temporal Dual-Depth Scoring (TDDS) for Enhanced Dataset Pruning
Xin Zhang, Jiawei Du, Yunsong Li +2
Dataset pruning aims to construct a coreset capable of achieving performance comparable to the original, full dataset. Most existing dataset pruning methods rely on snapshot-based…
Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation
Jiawei Du, Yidi Jiang, Vincent Y. F. Tan +2
Model-based deep learning has achieved astounding successes due in part to the availability of large-scale real-world data. However, processing such massive amounts of data comes a…
Sharpness-Aware Training for Free
Jiawei Du, Daquan Zhou, Jiashi Feng +2
Modern deep neural networks (DNNs) have achieved state-of-the-art performances but are typically over-parameterized. The over-parameterization may result in undesirably large gener…
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Jiawei Du, Hanshu Yan, Jiashi Feng +4
Overparametrized Deep Neural Networks (DNNs) often achieve astounding performances, but may potentially result in severe generalization error. Recently, the relation between the sh…
A Research on Cross-sectional Return Dispersion and Volatility of US Stock Market during COVID-19
Jiawei Du
We studied the volatility and cross-sectional return dispersion effect of S&P Health Care Sector under the covid-19 epidemic. We innovatively used the Google index to proxy the imp…
RAIN: A Simple Approach for Robust and Accurate Image Classification Networks
Jiawei Du, Hanshu Yan, Vincent Y. F. Tan +3
It has been shown that the majority of existing adversarial defense methods achieve robustness at the cost of sacrificing prediction accuracy. The undesirable severe drop in accura…
On Robustness of Neural Ordinary Differential Equations
Hanshu Yan, Jiawei Du, Vincent Y. F. Tan +1
Neural ordinary differential equations (ODEs) have been attracting increasing attention in various research domains recently. There have been some works studying optimization issue…
Query-efficient Meta Attack to Deep Neural Networks
Jiawei Du, Hu Zhang, Joey Tianyi Zhou +2
Black-box attack methods aim to infer suitable attack patterns to targeted DNN models by only using output feedback of the models and the corresponding input queries. However, due…