27 citations · 40 across the 16 of their papers we have counts for
7 papers · 1 filter
WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor Attacks Against Deep Neural Networks
Jun Xia, Zhihao Yue, Yingbo Zhou +3
Due to the popularity of Artificial Intelligence (AI) technology, numerous backdoor attacks are designed by adversaries to mislead deep neural network predictions by manipulating t…
Continual Learning via Manifold Expansion Replay
Zihao Xu, Xuan Tang, Yufei Shi +4
In continual learning, the learner learns multiple tasks in sequence, with data being acquired only once for each task. Catastrophic forgetting is a major challenge to continual le…
EqGAN: Feature Equalization Fusion for Few-shot Image Generation
Yingbo Zhou, Zhihao Yue, Yutong Ye +3
Due to the absence of fine structure and texture information, existing fusion-based few-shot image generation methods suffer from unsatisfactory generation quality and diversity. T…
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination
Ming Hu, Zhihao Yue, Xiaofei Xie +6
Although Federated Learning (FL) enables global model training across clients without compromising their raw data, due to the unevenly distributed data among clients, existing Fede…
Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations
Jianzhang Zheng, Hao Shen, Jian Yang +5
Autoencoders have achieved great success in various computer vision applications. The autoencoder learns appropriate low dimensional image representations through the self-supervis…
A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold
Yanhong Fei, Xian Wei, Yingjie Liu +2
Although Deep Learning (DL) has achieved success in complex Artificial Intelligence (AI) tasks, it suffers from various notorious problems (e.g., feature redundancy, and vanishing…
CyclicFL: A Cyclic Model Pre-Training Approach to Efficient Federated Learning
Pengyu Zhang, Yingbo Zhou, Ming Hu +2
Federated learning (FL) has been proposed to enable distributed learning on Artificial Intelligence Internet of Things (AIoT) devices with guarantees of high-level data privacy. Si…