| Deformable convolutional networks J Dai, H Qi, Y Xiong, Y Li, G Zhang, H Hu, Y Wei International Conference on Computer Vision, 2017 | 1665 | 2017 |
| Benchmarking Model-Based Reinforcement Learning T Wang, X Bao, I Clavera, J Hoang, Y Wen, E Langlois, S Zhang, G Zhang, ... | 116* | 2019 |
| Noisy Natural Gradient as Variational Inference G Zhang, S Sun, D Duvenaud, R Grosse International Conference on Machine Learning, 2018 | 108 | 2018 |
| Functional Variational Bayesian Neural Networks S Sun, G Zhang, J Shi, R Grosse International Conference on Learning Representations, 2019 | 96 | 2019 |
| Three Mechanisms of Weight Decay Regularization G Zhang, C Wang, B Xu, R Grosse International Conference on Learning Representations, 2019 | 89 | 2019 |
| Picking Winning Tickets Before Training by Preserving Gradient Flow C Wang, G Zhang, R Grosse International Conference on Learning Representations, 2020 | 58 | 2020 |
| 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 | 42 | 2018 |
| On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach Y Wang, G Zhang, J Ba International Conference on Learning Representations, 2020 | 32 | 2020 |
| Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks G Zhang, J Martens, R Grosse Advances in Neural Information Processing Systems, 2019 | 31 | 2019 |
| 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 | 30 | 2019 |
| EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis C Wang, R Grosse, S Fidler, G Zhang International Conference on Machine Learning, 2019 | 25 | 2019 |
| Eigenvalue Corrected Noisy Natural Gradient J Bae, G Zhang, R Grosse Neural Information Processing Systems (Bayesian Deep Learning Workshop), 2018 | 13 | 2018 |
| 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 | 12* | 2020 |
| A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints G Zhang, X Bao, L Lessard, R Grosse arXiv preprint arXiv:2009.11359, 2020 | 3 | 2020 |
| Nonnegative matrix cofactorization for weakly supervised image parsing G Zhang, X Gong IEEE Signal Processing Letters 23 (11), 1682-1686, 2016 | 3 | 2016 |
| On the suboptimality of negative momentum for minimax optimization G Zhang, Y Wang International Conference on Artificial Intelligence and Statistics, 2020 | 2 | 2020 |
| Don't Fix What ain't Broke: Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization G Zhang, Y Wang, L Lessard, R Grosse arXiv preprint arXiv:2102.09468, 2021 | | 2021 |
Roger GrosseAssistant Professor, University of TorontoVerified email at cs.toronto.edu
