118 citations · 809 across the 58 of their papers we have counts for
4 papers · 1 filter
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks
Zhen Dong, Zhewei Yao, Yaohui Cai +4
Quantization is an effective method for reducing memory footprint and inference time of Neural Networks, e.g., for efficient inference in the cloud, especially at the edge. However…
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data
Ali Eshragh, Fred Roosta, Asef Nazari +1
We apply methods from randomized numerical linear algebra (RandNLA) to develop improved algorithms for the analysis of large-scale time series data. We first develop a new fast alg…
ANODEV2: A Coupled Neural ODE Evolution Framework
Tianjun Zhang, Zhewei Yao, Amir Gholami +4
It has been observed that residual networks can be viewed as the explicit Euler discretization of an Ordinary Differential Equation (ODE). This observation motivated the introducti…
HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision
Zhen Dong, Zhewei Yao, Amir Gholami +2
Model size and inference speed/power have become a major challenge in the deployment of Neural Networks for many applications. A promising approach to address these problems is qua…