activity
20182022
most citedGenerative and Discriminative Learning for Distorted Image Restoration

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2022

On Understanding and Mitigating the Dimensional Collapse of Graph Contrastive Learning: a Non-Maximum Removal Approach

Jiawei Sun, Ruoxin Chen, Jie Li +3

Graph Contrastive Learning (GCL) has shown promising performance in graph representation learning (GRL) without the supervision of manual annotations. GCL can generate graph-level…

eess.IV20202 cited

Generative and Discriminative Learning for Distorted Image Restoration

Yi Gu, Yuting Gao, Jie Li +2

Liquify is a common technique for image editing, which can be used for image distortion. Due to the uncertainty in the distortion variation, restoring distorted images caused by li…

cs.CV2020

Association: Remind Your GAN not to Forget

Yi Gu, Jie Li, Yuting Gao +5

Neural networks are susceptible to catastrophic forgetting. They fail to preserve previously acquired knowledge when adapting to new tasks. Inspired by human associative memory sys…

cs.LG2020

A Framework of Randomized Selection Based Certified Defenses Against Data Poisoning Attacks

Ruoxin Chen, Jie Li, Chentao Wu +2

Neural network classifiers are vulnerable to data poisoning attacks, as attackers can degrade or even manipulate their predictions thorough poisoning only a few training samples. H…

cs.DC2018

FDRC: Flow-Driven Rule Caching Optimization in Software Defined Networking

He Li, Song Guo, Chentao Wu +1

With the sharp growth of cloud services and their possible combinations, the scale of data center network traffic has an inevitable explosive increasing in recent years. Software d…