Guodong Zhang - RankMe

32 papers A* 8A 3Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	—	`—`	Deep Learning Dynamics: From Minimization to Games Guodong Zhang
2022	A	`conf`	Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization. AISTATS Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger B. Grosse
2021	J	`jnl`	A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints. J. Mach. Learn. Res. Guodong Zhang, Xuchan Bao, Laurent Lessard, Roger B. Grosse
2021	A*	`conf`	Differentiable Annealed Importance Sampling and the Perils of Gradient Noise. NeurIPS Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B. Grosse
2021	J	`jnl`	Differentiable Annealed Importance Sampling and the Perils of Gradient Noise. CoRR Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B. Grosse
2021	J	`jnl`	Don't Fix What ain't Broke: Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization. CoRR Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger B. Grosse
2021	J	`jnl`	Learning to Give Checkable Answers with Prover-Verifier Games. CoRR Cem Anil, Guodong Zhang, Yuhuai Wu, Roger B. Grosse
2021	A	`conf`	On the Suboptimality of Negative Momentum for Minimax Optimization. AISTATS Guodong Zhang, Yuanhao Wang
2020	J	`jnl`	A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints. CoRR Guodong Zhang, Xuchan Bao, Laurent Lessard, Roger B. Grosse
2020	A	`conf`	An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. AISTATS Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
2020	A*	`conf`	On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. ICLR Yuanhao Wang, Guodong Zhang, Jimmy Ba
2020	J	`jnl`	On the Suboptimality of Negative Momentum for Minimax Optimization. CoRR Guodong Zhang, Yuanhao Wang
2020	A*	`conf`	Picking Winning Tickets Before Training by Preserving Gradient Flow. ICLR Chaoqi Wang, Guodong Zhang, Roger B. Grosse
2020	J	`jnl`	Picking Winning Tickets Before Training by Preserving Gradient Flow. CoRR Chaoqi Wang, Guodong Zhang, Roger Baker Grosse
2019	J	`jnl`	Benchmarking Model-Based Reinforcement Learning. CoRR Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric D. Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba
2019	A*	`conf`	EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis. ICML Chaoqi Wang, Roger B. Grosse, Sanja Fidler, Guodong Zhang
2019	J	`jnl`	EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis. CoRR Chaoqi Wang, Roger B. Grosse, Sanja Fidler, Guodong Zhang
2019	A*	`conf`	Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks. NeurIPS Guodong Zhang, James Martens, Roger B. Grosse
2019	J	`jnl`	Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks. CoRR Guodong Zhang, James Martens, Roger B. Grosse
2019	J	`jnl`	Functional Variational Bayesian Neural Networks. CoRR Shengyang Sun, Guodong Zhang, Jiaxin Shi, Roger B. Grosse
2019	—	`conf`	Functional variational Bayesian Neural Networks. ICLR (Poster) Shengyang Sun, Guodong Zhang, Jiaxin Shi, Roger B. Grosse
2019	J	`jnl`	Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. CoRR Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
2019	J	`jnl`	On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. CoRR Yuanhao Wang, Guodong Zhang, Jimmy Ba
2019	—	`conf`	Three Mechanisms of Weight Decay Regularization. ICLR (Poster) Guodong Zhang, Chaoqi Wang, Bowen Xu, Roger B. Grosse
2019	A*	`conf`	Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. NeurIPS Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse
2019	J	`jnl`	Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. CoRR Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse
2018	A*	`conf`	Differentiable Compositional Kernel Learning for Gaussian Processes. ICML Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger B. Grosse
2018	J	`jnl`	Differentiable Compositional Kernel Learning for Gaussian Processes. CoRR Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger B. Grosse
2018	J	`jnl`	Eigenvalue Corrected Noisy Natural Gradient. CoRR Juhan Bae, Guodong Zhang, Roger B. Grosse
2018	A*	`conf`	Noisy Natural Gradient as Variational Inference. ICML Guodong Zhang, Shengyang Sun, David Duvenaud, Roger B. Grosse
2018	J	`jnl`	Three Mechanisms of Weight Decay Regularization. CoRR Guodong Zhang, Chaoqi Wang, Bowen Xu, Roger B. Grosse
2017	J	`jnl`	Noisy Natural Gradient as Variational Inference. CoRR Guodong Zhang, Shengyang Sun, David Duvenaud, Roger B. Grosse