26 citations · 39 across the 9 of their papers we have counts for
9 papers
SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing
Sheng Li, Geng Yuan, Yue Dai +3
There has been a proliferation of artificial intelligence applications, where model training is key to promising high-quality services for these applications. However, the model tr…
Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training
Geng Yuan, Yanyu Li, Sheng Li +5
Recently, sparse training has emerged as a promising paradigm for efficient deep learning on edge devices. The current research mainly devotes efforts to reducing training costs by…
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System
Zhendong Wang, Xiaoming Zeng, Xulong Tang +3
The deep neural network (DNN) models are deemed confidential due to their unique value in expensive training efforts, privacy-sensitive training data, and proprietary network chara…
Sustainable AI Processing at the Edge
Sébastien Ollivier, Sheng Li, Yue Tang +5
Edge computing is a popular target for accelerating machine learning algorithms supporting mobile devices without requiring the communication latencies to handle them in the cloud.…
Automated Runtime-Aware Scheduling for Multi-Tenant DNN Inference on GPU
Fuxun Yu, Shawn Bray, Di Wang +4
With the fast development of deep neural networks (DNNs), many real-world applications are adopting multiple models to conduct compound tasks, such as co-running classification, de…
Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration
Yifan Gong, Geng Yuan, Zheng Zhan +9
Weight pruning is an effective model compression technique to tackle the challenges of achieving real-time deep neural network (DNN) inference on mobile devices. However, prior pru…
A Survey of Large-Scale Deep Learning Serving System Optimization: Challenges and Opportunities
Fuxun Yu, Di Wang, Longfei Shangguan +4
Deep Learning (DL) models have achieved superior performance in many application domains, including vision, language, medical, commercial ads, entertainment, etc. With the fast dev…
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design
Yuxuan Cai, Hongjia Li, Geng Yuan +5
The rapid development and wide utilization of object detection techniques have aroused attention on both accuracy and speed of object detectors. However, the current state-of-the-a…
Exploration of Input Patterns for Enhancing the Performance of Liquid State Machines
Shasha Guo, Lianhua Qu, Lei Wang +3
Spiking Neural Networks (SNN) have gained increasing attention for its low power consumption. But training SNN is challenging. Liquid State Machine (LSM), as a major type of Reserv…