11 citations · 15 across the 3 of their papers we have counts for
4 papers · 1 filter
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration
Zirui Xu, Fuxun Yu, Jinjun Xiong +1
In this paper, we propose Helios, a heterogeneity-aware FL framework to tackle the straggler issue. Helios identifies individual devices' heterogeneous training capability, and the…
Multi-stage Deep Classifier Cascades for Open World Recognition
Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu +4
At present, object recognition studies are mostly conducted in a closed lab setting with classes in test phase typically in training phase. However, real-world problem is far more…
Interpreting and Evaluating Neural Network Robustness
Fuxun Yu, Zhuwei Qin, Chenchen Liu +3
Recently, adversarial deception becomes one of the most considerable threats to deep neural networks. However, compared to extensive research in new designs of various adversarial…
DoPa: A Comprehensive CNN Detection Methodology against Physical Adversarial Attacks
Zirui Xu, Fuxun Yu, Xiang Chen
Recently, Convolutional Neural Networks (CNNs) demonstrate a considerable vulnerability to adversarial attacks, which can be easily misled by adversarial perturbations. With more a…