3 citations · 7 across the 5 of their papers we have counts for
6 papers
Design and Analysis of Uplink and Downlink Communications for Federated Learning
Sihui Zheng, Cong Shen, Xiang Chen
Communication has been known to be one of the primary bottlenecks of federated learning (FL), and yet existing studies have not addressed the efficient communication design, partic…
Third ArchEdge Workshop: Exploring the Design Space of Efficient Deep Neural Networks
Fuxun Yu, Dimitrios Stamoulis, Di Wang +2
This paper gives an overview of our ongoing work on the design space exploration of efficient deep neural networks (DNNs). Specifically, we cover two aspects: (1) static architectu…
Efficient Neural Network Implementation with Quadratic Neuron
Zirui Xu, Jinjun Xiong, Fuxun Yu +1
Previous works proved that the combination of the linear neuron network with nonlinear activation functions (e.g. ReLu) can achieve nonlinear function approximation. However, simpl…
LanCe: A Comprehensive and Lightweight CNN Defense Methodology against Physical Adversarial Attacks on Embedded Multimedia Applications
Zirui Xu, Fuxun Yu, Xiang Chen
Recently, adversarial attacks can be applied to the physical world, causing practical issues to various Convolutional Neural Networks (CNNs) powered applications. Most existing phy…
Task-Adaptive Incremental Learning for Intelligent Edge Devices
Zhuwei Qin, Fuxun Yu, Xiang Chen
Convolutional Neural Networks (CNNs) are used for a wide range of image-related tasks such as image classification and object detection. However, a large pre-trained CNN model cont…
Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation
Xiaolong Ma, Geng Yuan, Sheng Lin +6
The state-of-art DNN structures involve intensive computation and high memory storage. To mitigate the challenges, the memristor crossbar array has emerged as an intrinsically suit…