Guodong Zhang
Guodong Zhang
Ph.D. student, University of Toronto
在 cs.toronto.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Deformable convolutional networks
J Dai, H Qi, Y Xiong, Y Li, G Zhang, H Hu, Y Wei
International Conference on Computer Vision, 2017
10632017
Noisy Natural Gradient as Variational Inference
G Zhang, S Sun, D Duvenaud, R Grosse
International Conference on Machine Learning, 2018
582018
Benchmarking Model-Based Reinforcement Learning
T Wang, X Bao, I Clavera, J Hoang, Y Wen, E Langlois, S Zhang, G Zhang, ...
57*2019
Functional Variational Bayesian Neural Networks
S Sun, G Zhang, J Shi, R Grosse
International Conference on Learning Representations, 2019
442019
Three Mechanisms of Weight Decay Regularization
G Zhang, C Wang, B Xu, R Grosse
International Conference on Learning Representations, 2019
442019
Differentiable Compositional Kernel Learning for Gaussian Processes
S Sun, G Zhang, C Wang, W Zeng, J Li, R Grosse
International Conference on Machine Learning, 2018
242018
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks
G Zhang, J Martens, R Grosse
Advances in Neural Information Processing Systems, 2019
202019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
G Zhang, L Li, Z Nado, J Martens, S Sachdeva, GE Dahl, CJ Shallue, ...
Advances in Neural Information Processing Systems, 2019
132019
Picking Winning Tickets Before Training by Preserving Gradient Flow
C Wang, G Zhang, R Grosse
International Conference on Learning Representations, 2020
122020
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
C Wang, R Grosse, S Fidler, G Zhang
International Conference on Machine Learning, 2019
112019
Eigenvalue Corrected Noisy Natural Gradient
J Bae, G Zhang, R Grosse
Neural Information Processing Systems (Bayesian Deep Learning Workshop), 2018
82018
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise
Y Wen, K Luk, M Gazeau, G Zhang, H Chan, J Ba
International Conference on Artificial Intelligence and Statistics, 3621-3631, 2020
7*2020
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
Y Wang, G Zhang, J Ba
International Conference on Learning Representations, 2020
62020
Nonnegative matrix cofactorization for weakly supervised image parsing
G Zhang, X Gong
IEEE Signal Processing Letters 23 (11), 1682-1686, 2016
32016
系统目前无法执行此操作,请稍后再试。
文章 1–14