Ahmet Alacaoglu
15 papers · 2017–2025 · 6 venues · across top CS/AI venues
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Research topics
Keywords
stochastic optimization
(4)
variance reduction
(4)
constrained optimization
(3)
moreau envelope
(3)
sample complexity
(3)
convex optimization
(3)
non-convex optimization
(2)
stochastic gradient
(2)
coordinate descent
(2)
variational inequality
(2)
monotone inclusion
(2)
markov chain monte carlo
(1)
finite-sum optimization
(1)
nash equilibrium
(1)
convergence analysis
(1)
primal-dual optimization
(1)
stochastic gradient descent
(1)
gradient descent
(1)
online convex optimization
(1)
natural actor-critic
(1)
Papers
Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
ICML 2025
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints
AISTATS 2024
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
ICML 2024
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
ICLR 2024
Beyond the Golden Ratio for Variational Inequality Algorithms
JMLR 2023
Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data
ICML 2023
A Natural Actor-Critic Framework for Zero-Sum Markov Games
ICML 2022
Stochastic Variance Reduction for Variational Inequality Methods
COLT 2022
Convergence of adaptive algorithms for constrained weakly convex optimization
NeurIPS 2021
A new regret analysis for Adam-type algorithms
ICML 2020
Conditional gradient methods for stochastically constrained convex minimization
ICML 2020
Random extrapolation for primal-dual coordinate descent
ICML 2020
Almost surely constrained convex optimization
ICML 2019
An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints
NeurIPS 2019
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization
NeurIPS 2017