Robert M. Gower

Flatiron Health (United States) — United States

Computer Science · Physical Sciences

13h-index544citations72works0.12yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Stochastic Gradient Optimization Techniques(42), Sparse and Compressive Sensing Techniques(32), Advanced Optimization Algorithms Research(12), Matrix Theory and Algorithms(11), Markov Chains and Monte Carlo Methods(7)

Publications70 total

BPS2026 – Parsimonious recovery of cryo-EM ensemble probabilities
Biophysical Journal·2026
Schedulers for Schedule-free: Theoretically inspired hyperparameters
arXiv (Cornell University)·2025Open Access
The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm
arXiv (Cornell University)·2025Open Access
Enhancing Policy Gradient with the Polyak Step-Size Adaption
arXiv (Cornell University)·2024Open Access
Correction: A Bregman–Kaczmarz method for nonlinear systems of equations
Computational Optimization and Applications·2024Open Access
Directional Smoothness and Gradient Methods: Convergence and Adaptivity
arXiv (Cornell University)·2024Open Access
Level Set Teleportation: An Optimization Perspective
arXiv (Cornell University)·2024Open Access
Batch and match: black-box variational inference with a score-based divergence
arXiv (Cornell University)·2024Open Access
Tracking the Median of Gradients with a Stochastic Proximal Point Method
arXiv (Cornell University)·2024Open Access
Directional Smoothness and Gradient Methods: Convergence and Adaptivity
2024· 1 cited
EigenVI: score-based variational inference with orthogonal function expansions
2024
SANIA: Polyak-type Optimization Framework Leads to Scale Invariant Stochastic Algorithms
arXiv (Cornell University)·2023Open Access
A Bregman–Kaczmarz method for nonlinear systems of equations
Computational Optimization and Applications·2023· 11 cited
Unified Analysis of Stochastic Gradient Methods for Composite Convex and Smooth Optimization
Journal of Optimization Theory and Applications·2023· 19 cited
Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM
arXiv (Cornell University)·2023· 1 citedOpen Access
Variational Inference with Gaussian Score Matching
arXiv (Cornell University)·2023· 1 citedOpen Access
A Model-Based Method for Minimizing CVaR and Beyond
arXiv (Cornell University)·2023· 1 citedOpen Access
Improving Convergence and Generalization Using Parameter Symmetries
arXiv (Cornell University)·2023Open Access
MoMo: Momentum Models for Adaptive Learning Rates
arXiv (Cornell University)·2023Open Access
A Bregman-Kaczmarz method for nonlinear systems of equations
arXiv (Cornell University)·2023Open Access
page 1 of 4Next →

Frequent Co-authors

Peter Richtárik(13), Othmane Sebbouh(8), Aaron Defazio(8), Rui Yuan(5), Nicolas Loizou(4), Alessandro Lazaric(4), Artur L. Gower(3), Francis Bach(3), Nidham Gazagnadou(3), Denali Molitor(2), Jacob D. Moorman(2), Deanna Needell(2), Zheng Wang(2), Yili Xia(2), Yongming Huang(2), Ahmed Khaled(2), Guillaume Garrigos(2), Margarida Pinheiro Mello(2), Brahim Khalil Abid(2), Jonathan Deakin(2)