13 citations · 58 across the 13 of their papers we have counts for
6 papers · 1 filter
Distributed Pruning Towards Tiny Neural Networks in Federated Learning
Hong Huang, Lan Zhang, Chaoyue Sun +3
Neural network pruning is an essential technique for reducing the size and complexity of deep neural networks, enabling large-scale models on devices with limited resources. Howeve…
Federated Semi-Supervised Domain Adaptation via Knowledge Transfer
Madhureeta Das, Xianhao Chen, Xiaoyong Yuan +1
Given the rapidly changing machine learning environments and expensive data labeling, semi-supervised domain adaptation (SSDA) is imperative when the labeled data from the source d…
Towards Robust On-Ramp Merging via Augmented Multimodal Reinforcement Learning
Gaurav Bagwe, Jian Li, Xiaoyong Yuan +1
Despite the success of AI-enabled onboard perception, on-ramp merging has been one of the main challenges for autonomous driving. Due to limited sensing range of onboard sensors, a…
Residue-based Label Protection Mechanisms in Vertical Logistic Regression
Juntao Tan, Lan Zhang, Yang Liu +2
Federated learning (FL) enables distributed participants to collaboratively learn a global model without revealing their private data to each other. Recently, vertical FL, where th…
Pay "Attention" to Adverse Weather: Weather-aware Attention-based Object Detection
Saket S. Chaturvedi, Lan Zhang, Xiaoyong Yuan
Despite the recent advances of deep neural networks, object detection for adverse weather remains challenging due to the poor perception of some sensors in adverse weather. Instead…
Membership Inference Attacks and Defenses in Neural Network Pruning
Xiaoyong Yuan, Lan Zhang
Neural network pruning has been an essential technique to reduce the computation and memory requirements for using deep neural networks for resource-constrained devices. Most exist…