54 citations · 78 across the 4 of their papers we have counts for
4 papers
VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization
Cheng Gong, Yao Chen, Ye Lu +3
Quantization has been proven to be an effective method for reducing the computing and/or storage cost of DNNs. However, the trade-off between the quantization bitwidth and final ac…
EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions
Yuhong Li, Cong Hao, Xiaofan Zhang +5
High quality AI solutions require joint optimization of AI algorithms and their hardware implementations. In this work, we are the first to propose a fully simultaneous, efficient…
NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving
Cong Hao, Yao Chen, Xinheng Liu +9
The rapidly growing demands for powerful AI algorithms in many application domains have motivated massive investment in both high-quality deep neural network (DNN) models and high-…
A Bi-Directional Co-Design Approach to Enable Deep Learning on IoT Devices
Xiaofan Zhang, Cong Hao, Yuhong Li +4
Developing deep learning models for resource-constrained Internet-of-Things (IoT) devices is challenging, as it is difficult to achieve both good quality of results (QoR), such as…