Gower, Robert M.

25 publications

NeurIPS 2025 Fisher Meets Feynman: Score-Based Variational Inference with a Product of Experts Diana Cai, Robert M. Gower, David Blei, Lawrence K. Saul

NeurIPS 2025 In Search of Adam’s Secret Sauce Antonio Orvieto, Robert M. Gower

AISTATS 2025 Level Set Teleportation: An Optimization Perspective Aaron Mishkin, Alberto Bietti, Robert M. Gower

TMLR 2025 Tracking the Median of Gradients with a Stochastic Proximal Point Method Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower

ICML 2024 Batch and Match: Black-Box Variational Inference with a Score-Based Divergence Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles Margossian, Robert M. Gower, David Blei, Lawrence K. Saul

NeurIPS 2024 Directional Smoothness and Gradient Methods: Convergence and Adaptivity Aaron Mishkin, Ahmed Khaled, Yuanhao Wang, Aaron Defazio, Robert M. Gower

NeurIPS 2024 EigenVI: Score-Based Variational Inference with Orthogonal Function Expansions Diana Cai, Chirag Modi, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul

ICMLW 2024 EigenVI: Score-Based Variational Inference with Orthogonal Function Expansions Diana Cai, Chirag Modi, Charles Margossian, Robert M. Gower, David Blei, Lawrence K. Saul

ICLR 2024 Improving Convergence and Generalization Using Parameter Symmetries Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu

ICML 2024 MoMo: Momentum Models for Adaptive Learning Rates Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio, Robert M. Gower

ICML 2023 A Model-Based Method for Minimizing CVaR and Beyond Si Yi Meng, Robert M. Gower

NeurIPSW 2023 A Novel Analysis of Gradient Descent Under Directional Smoothness Aaron Mishkin, Ahmed Khaled, Aaron Defazio, Robert M. Gower

TMLR 2023 A Stochastic Proximal Polyak Step Size Fabian Schaipp, Robert M. Gower, Michael Ulbrich

NeurIPSW 2023 Level Set Teleportation: The Good, the Bad, and the Ugly Aaron Mishkin, Alberto Bietti, Robert M. Gower

ICLR 2023 Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies Rui Yuan, Simon Shaolei Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao

NeurIPSW 2023 Robust Gradient Estimation in the Presence of Heavy-Tailed Noise Fabian Schaipp, Umut Simsekli, Robert M. Gower

ICLR 2023 SP2 : A Second Order Stochastic Polyak Method Shuang Li, William Joseph Swartworth, Martin Takáč, Deanna Needell, Robert M. Gower

NeurIPSW 2023 Variance Reduced Model Based Methods: New Rates and Adaptive Step Sizes Robert M. Gower, Frederik Kunstner, Mark Schmidt

AISTATS 2022 A General Sample Complexity Analysis of Vanilla Policy Gradient Rui Yuan, Robert M. Gower, Alessandro Lazaric

AISTATS 2022 SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums Jiabin Chen, Rui Yuan, Guillaume Garrigos, Robert M. Gower

NeurIPSW 2022 A Stochastic Prox-Linear Method for CVaR Minimization Si Yi Meng, Vasileios Charisopoulos, Robert M. Gower

COLT 2021 Almost Sure Convergence Rates for Stochastic Gradient Descent and Stochastic Heavy Ball Othmane Sebbouh, Robert M Gower, Aaron Defazio

ACML 2021 The Power of Factorial Powers: New Parameter Settings for (Stochastic) Optimization Aaron Defazio, Robert M. Gower

AISTATS 2018 Stochastic Algorithms for Entropy-Regularized Optimal Transport Problems Brahim Khalil Abid, Robert M. Gower

AISTATS 2018 Tracking the Gradients Using the Hessian: A New Look at Variance Reducing Stochastic Methods Robert M. Gower, Nicolas Le Roux, Francis R. Bach