activity
20192022
most citedAnti-Bandit Neural Architecture Search for Model Defense

2 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20222 cited

Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning

Xiaoyue Duan, Guoliang Kang, Runqi Wang +4

Robust Model-Agnostic Meta-Learning (MAML) is usually adopted to train a meta-model which may fast adapt to novel classes with only a few exemplars and meanwhile remain robust to a…

cs.GT20221 cited

Competitive Online Truthful Time-Sensitive-Valued Data Auction

Shuangshuang Xue, Xiang-Yang Li

In this work, we investigate online mechanisms for trading time-sensitive valued data. We adopt a continuous function to represent the data value fluctuation over time .…

cs.CV2022

Associative Adversarial Learning Based on Selective Attack

Runqi Wang, Xiaoyue Duan, Baochang Zhang +4

A human's attention can intuitively adapt to corrupted areas of an image by recalling a similar uncorrupted image they have previously seen. This observation motivates us to improv…

cs.CV20202 cited

Anti-Bandit Neural Architecture Search for Model Defense

Hanlin Chen, Baochang Zhang, Song Xue +4

Deep convolutional neural networks (DCNNs) have dominated as the best performers in machine learning, but can be challenged by adversarial attacks. In this paper, we defend against…

eess.SP2019

To Learn or Not to Learn: Deep Learning Assisted Wireless Modem Design

S. Xue, A. Li, J. Wang +4

Deep learning is driving a radical paradigm shift in wireless communications, all the way from the application layer down to the physical layer. Despite this, there is an ongoing d…