activity
20202022
most citedVEGA: Towards an End-to-End Configurable AutoML Pipeline

6 citations · 9 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2022

When Neural Networks Fail to Generalize? A Model Sensitivity Perspective

Jiajin Zhang, Hanqing Chao, Amit Dhurandhar +4

Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions. This paper considers a more realistic yet more challenging scenari…

cs.LG2022

Model-based Reinforcement Learning with Multi-step Plan Value Estimation

Haoxin Lin, Yihao Sun, Jiaji Zhang +1

A promising way to improve the sample efficiency of reinforcement learning is model-based methods, in which many explorations and evaluations can happen in the learned models to sa…

eess.IV2021

Task-Oriented Low-Dose CT Image Denoising

Jiajin Zhang, Hanqing Chao, Xuanang Xu +3

The extensive use of medical CT has raised a public concern over the radiation dose to the patient. Reducing the radiation dose leads to increased CT image noise and artifacts, whi…

cs.CV20206 cited

VEGA: Towards an End-to-End Configurable AutoML Pipeline

Bochao Wang, Hang Xu, Jiajin Zhang +21

Automated Machine Learning (AutoML) is an important industrial solution for automatic discovery and deployment of the machine learning models. However, designing an integrated Auto…

cs.CV20203 cited

Robustified Domain Adaptation

Jiajin Zhang, Hanqing Chao, Pingkun Yan

Unsupervised domain adaptation (UDA) is widely used to transfer knowledge from a labeled source domain to an unlabeled target domain with different data distribution. While extensi…

cs.CV2020

Difference-in-Differences: Bridging Normalization and Disentanglement in PG-GAN

Xiao Liu, Jiajie Zhang, Siting Li +2

What mechanisms causes GAN's entanglement? Although developing disentangled GAN has attracted sufficient attention, it is unclear how entanglement is originated by GAN transformati…