Zhewei Yao
Zhewei Yao
Verified email at berkeley.edu - Homepage
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Cited by
Q-bert: Hessian based ultra low precision quantization of bert
S Shen, Z Dong, J Ye, L Ma, Z Yao, A Gholami, MW Mahoney, K Keutzer
AAAI 2020, 2019
Hawq: Hessian aware quantization of neural networks with mixed-precision
Z Dong*, Z Yao*, A Gholami*, MW Mahoney, K Keutzer
Proceedings of the IEEE/CVF International Conference on Computer Vision, 293-302, 2019
ZeroQ: A Novel Zero Shot Quantization Framework
Y Cai*, Z Yao*, Z Dong*, A Gholami, MW Mahoney, K Keutzer
CVPR 2020, 2020
Hessian-based analysis of large batch training and robustness to adversaries
Z Yao, A Gholami, Q Lei, K Keutzer, MW Mahoney
NeurIPS 2018, 2018
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks
Z Dong, Z Yao, Y Cai, D Arfeen, A Gholami, MW Mahoney, K Keutzer
Advances in Neural Information Processing Systems, Beyond First order Method …, 2019
Shallow neural networks for fluid flow reconstruction with limited sensors
NB Erichson, L Mathelin, Z Yao, SL Brunton, MW Mahoney, JN Kutz
Proceedings of the Royal Society A 476 (2238), 20200097, 2020
On the computational inefficiency of large batch sizes for stochastic gradient descent
N Golmant, N Vemuri, Z Yao, V Feinberg, A Gholami, K Rothauge, ...
arXiv preprint arXiv:1811.12941, 2018
ANODEV2: A coupled neural ODE framework
T Zhang*, Z Yao*, A Gholami*, J Gonzalez, K Keutzer, M Mahoney, ...
PyHessian: Neural networks through the lens of the Hessian
Z Yao, A Gholami, K Keutzer, M Mahoney
IEEE BigData, 2019
Large batch size training of neural networks with adversarial training and second-order information
Z Yao, A Gholami, D Arfeen, R Liaw, J Gonzalez, K Keutzer, M Mahoney
arXiv preprint arXiv:1810.01021, 2018
Inexact Nonconvex Newton-Type Methods
Z Yao, P Xu, F Roosta, MW Mahoney
Informs Journal on Optimization 3 (2), 154-182, 2021
Trust region based adversarial attack on neural networks
Z Yao, A Gholami, P Xu, K Keutzer, MW Mahoney
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Z Yao, A Gholami, S Shen, K Keutzer, MW Mahoney
AAAI 2021, 2020
Rethinking Batch Normalization in Transformers
S Shen*, Z Yao*, A Gholami, M Mahoney, K Keutzer
ICML2020, 2020
A TV-Gaussian prior for infinite-dimensional Bayesian inverse problems and its numerical implementations
Z Yao, Z Hu, J Li
Inverse Problems 32 (7), 075006, 2016
A survey of quantization methods for efficient neural network inference
A Gholami, S Kim, Z Dong, Z Yao, MW Mahoney, K Keutzer
arXiv preprint arXiv:2103.13630, 2021
On an adaptive preconditioned Crank–Nicolson MCMC algorithm for infinite dimensional Bayesian inference
Z Hu, Z Yao, J Li
Journal of Computational Physics 332, 492-503, 2017
Inefficiency of K-FAC for large batch size training
L Ma, G Montague, J Ye, Z Yao, A Gholami, K Keutzer, MW Mahoney
AAAI 2020, 2019
HAWQV3: Dyadic Neural Network Quantization
Z Yao, Z Dong, Z Zheng, A Gholami, J Yu, E Tan, L Wang, Q Huang, ...
ICML2021, 2020
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models
Z Zhang, Y Yang, Z Yao, Y Yan, JE Gonzalez, MW Mahoney
arXiv preprint arXiv:2008.11364, 2020
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