72 citations · 222 across the 12 of their papers we have counts for
9 papers · 1 filter
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
Jingwei Sun, Ang Li, Binghui Wang +3
Federated learning (FL) is a popular distributed learning framework that can reduce privacy risks by not explicitly sharing private data. However, recent works demonstrated that sh…
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Binghui Wang, Ang Li, Hai Li +1
Graph-based semi-supervised node classification (GraphSSC) has wide applications, ranging from networking and security to data mining and machine learning, etc. However, existing c…
Towards Latency-aware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
Fuxun Yu, Zirui Xu, Tong Shen +12
Despite the superb performance of State-Of-The-Art (SOTA) DNNs, the increasing computational cost makes them very challenging to meet real-time latency and accuracy requirements. A…
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
Houxiang Fan, Binghui Wang, Pan Zhou +6
Link prediction in dynamic graphs (LPDG) is an important research problem that has diverse applications such as online recommendations, studies on disease contagion, organizational…
Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function
Binghui Wang, Tianxiang Zhou, Minhua Lin +5
Graph neural network (GNN), the mainstream method to learn on graph data, is vulnerable to graph evasion attacks, where an attacker slightly perturbing the graph structure can fool…
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets
Ang Li, Jingwei Sun, Binghui Wang +4
Federated learning is a popular distributed machine learning paradigm with enhanced privacy. Its primary goal is learning a global model that offers good performance for the partic…
MVStylizer: An Efficient Edge-Assisted Video Photorealistic Style Transfer System for Mobile Phones
Ang Li, Chunpeng Wu, Yiran Chen +1
Recent research has made great progress in realizing neural style transfer of images, which denotes transforming an image to a desired style. Many users start to use their mobile p…
TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations
Ang Li, Yixiao Duan, Huanrui Yang +2
The success of deep learning partially benefits from the availability of various large-scale datasets. These datasets are often crowdsourced from individual users and contain priva…
Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Huanrui Yang, Minxue Tang, Wei Wen +5
Modern deep neural networks (DNNs) often require high memory consumption and large computational loads. In order to deploy DNN algorithms efficiently on edge or mobile devices, a s…