Robert M. Gower
12 papers · 2021–2025 · 5 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (19) π Conference Polyglot Β· Silver π Keyword Champion (2) π Triple Crown
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Research topics
Machine Learning
(12)
Optimization & Theory Β· Machine Learning
(12)
Deep Learning
(6)
Mathematics & Optimization
(6)
Optimization
(6)
Reinforcement Learning
(2)
Methods
(2)
Models
(2)
Optimization & Theory Β· Deep Learning
(2)
Application Areas
(1)
Architectures
(1)
Core Methods
(1)
Learning Paradigms
(1)
Learning Types
(1)
Mathematics
(1)
Keywords
convergence rate
(4)
non-convex optimization
(3)
hessian-vector product
(2)
sample complexity
(2)
variance reduction
(2)
gradient descent
(2)
variational inference
(1)
probabilistic modeling
(1)
stochastic gradient descent
(1)
natural policy gradient
(1)
convergence analysis
(1)
matrix completion
(1)
neural network optimization
(1)
markov decision process
(1)
policy gradient
(1)
convergence
(1)
worst-case performance
(1)
logistic regression
(1)
convex optimization
(1)
finite-sum optimization
(1)
Papers
Level Set Teleportation: An Optimization Perspective
AISTATS 2025
Batch and match: black-box variational inference with a score-based divergence
ICML 2024
Directional Smoothness and Gradient Methods: Convergence and Adaptivity
NeurIPS 2024
EigenVI: score-based variational inference with orthogonal function expansions
NeurIPS 2024
Improving Convergence and Generalization Using Parameter Symmetries
ICLR 2024
MoMo: Momentum Models for Adaptive Learning Rates
ICML 2024
A Model-Based Method for Minimizing CVaR and Beyond
ICML 2023
Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies
ICLR 2023
SP2 : A Second Order Stochastic Polyak Method
ICLR 2023
A general sample complexity analysis of vanilla policy gradient
AISTATS 2022
SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums
AISTATS 2022
The Power of Factorial Powers: New Parameter settings for (Stochastic) Optimization
ACML 2021