Intelligence Fusion Laboratory
Electrical and Computer Engineering | George Mason University
News about the lab’s conference attendance.
– Dr. Chen attended the 55th Design Automation Conference (DAC) 2018 at San Francisco CA.
– Zirui presented poster of “DiReCt: Resource-Aware Dynamic Model Reconfiguration for Convolutional Neural Network in Mobile Systems”
– Fuxun presented poster of “ASP:A Fast Adversarial Attack Example Generation Framework based on Adversarial Saliency Prediction”
– Dr. Chen, attended the Second Association of Chinese Scholars in Computing (ACSIC) Symposium on Frontiers in Computing (SOFC DAC) 2018 at Dallas TX.
– Dr. Chen participated the Future Chip Forum 2017 hosted by the Tsinghua University.
– Dr. Chen hosted the Caffe2 Tutorial with Dr. Yangqing Jia and Dr. at the Tsinghua University.
– Dr. Chen attended the 36th International Conference On Computer Aided Design (ICCAD) 2017 at Irvine CA.
– Dr. Chen also presented the paper of “VoCaM: Visualization Oriented Convolutional Neural Network Acceleration on Mobile System.”
– Dr. Chen and Zhuwei Qin attend the ACM International Conference on Nanoscale Computing and Communication (NanoCom) at Arlington VA.
– Zhuwei also presented the paper of “Brain-Inspired Computing Accelerated by Memristor Technology”.
– One Invited Paper was accepted by the 36th International Conference on Computer-Aided Design (ICCAD) 2017.
“VoCaM: Visualization Oriented Convolutional Neural Network Acceleration on Mobile System”
– One Paper was accepted by the 30th International System On-Chip Conference (SoCC) 2017.
“MobiCore: An Adaptive Hybrid Approach for Power-Efficient CPU Management on Android Devices”
– Dr. Chen attended the 54th Design Automation Conference (DAC) 2017 at Austin TX.
– Dr. Chen attended the poster of “Efficient Deployment of Structurally Pruned DNNs on Distributed Mobile Systems”
– Two Papers was accepted by the 36th International Conference on Computer-Aided Design (ICCAD) 2017.
“MeDNN: A Distributed Mobile System with Enhanced Partition and Deployment for Large-Scale DNNs”
“AdaLearner: An Adaptive Distributed Mobile Learning System for Neural Networks”