Zhang, Guodong

19 publications

ICLR 2023 Deep Transformers Without Shortcuts: Modifying Self-Attention for Faithful Signal Propagation Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L Smith, Yee Whye Teh

TMLR 2023 Finding and Only Finding Differential Nash Equilibria by Both Pretending to Be a Follower Xuchan Bao, Guodong Zhang

AISTATS 2022 Near-Optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger B. Grosse

ICLR 2022 Deep Learning Without Shortcuts: Shaping the Kernel with Tailored Rectifiers Guodong Zhang, Aleksandar Botev, James Martens

ICLRW 2022 Finding and Only Finding Local Nash Equilibria by Both Pretending to Be a Follower Xuchan Bao, Guodong Zhang

AISTATS 2021 On the Suboptimality of Negative Momentum for Minimax Optimization Guodong Zhang, Yuanhao Wang

JMLR 2021 A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints Guodong Zhang, Xuchan Bao, Laurent Lessard, Roger Grosse

NeurIPS 2021 Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B Grosse

AISTATS 2020 An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba

ICLR 2020 On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach Yuanhao Wang, Guodong Zhang, Jimmy Ba

ICLR 2020 Picking Winning Tickets Before Training by Preserving Gradient Flow Chaoqi Wang, Guodong Zhang, Roger Grosse

ICML 2019 EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis Chaoqi Wang, Roger Grosse, Sanja Fidler, Guodong Zhang

NeurIPS 2019 Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks Guodong Zhang, James Martens, Roger B Grosse

ICLR 2019 Functional Variational Bayesian Neural Networks Shengyang Sun, Guodong Zhang, Jiaxin Shi, Roger Grosse

ICLR 2019 Three Mechanisms of Weight Decay Regularization Guodong Zhang, Chaoqi Wang, Bowen Xu, Roger Grosse

NeurIPS 2019 Which Algorithmic Choices Matter at Which Batch Sizes? Insights from a Noisy Quadratic Model Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George Dahl, Chris Shallue, Roger B Grosse

ICML 2018 Differentiable Compositional Kernel Learning for Gaussian Processes Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger Grosse

ICML 2018 Noisy Natural Gradient as Variational Inference Guodong Zhang, Shengyang Sun, David Duvenaud, Roger Grosse

ICCV 2017 Deformable Convolutional Networks Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, Yichen Wei