12 citations · 25 across the 4 of their papers we have counts for
4 papers
Contrastive Learning with Consistent Representations
Zihu Wang, Yu Wang, Zhuotong Chen +2
Contrastive learning demonstrates great promise for representation learning. Data augmentations play a critical role in contrastive learning by providing informative views of the d…
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning
Bicheng Ying, Kun Yuan, Hanbin Hu +2
Decentralized algorithm is a form of computation that achieves a global goal through local dynamics that relies on low-cost communication between directly-connected agents. On larg…
Exponential Graph is Provably Efficient for Decentralized Deep Training
Bicheng Ying, Kun Yuan, Yiming Chen +3
Decentralized SGD is an emerging training method for deep learning known for its much less (thus faster) communication per iteration, which relaxes the averaging step in parallel S…
Global Adversarial Attacks for Assessing Deep Learning Robustness
Hanbin Hu, Mit Shah, Jianhua Z. Huang +1
It has been shown that deep neural networks (DNNs) may be vulnerable to adversarial attacks, raising the concern on their robustness particularly for safety-critical applications.…