Ahmet Alacaoglu

According to our database, Ahmet Alacaoglu authored at least 21 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity.

Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright

CoRR, 2024

2023

Beyond the Golden Ratio for Variational Inequality Algorithms.

Ahmet Alacaoglu, Axel Böhm, Yura Malitsky

J. Mach. Learn. Res., 2023

Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints.

Ahmet Alacaoglu, Stephen J. Wright

CoRR, 2023

Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions.

Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas

CoRR, 2023

Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data.

Ahmet Alacaoglu, Hanbaek Lyu

Proceedings of the International Conference on Machine Learning, 2023

2022

On the Convergence of Stochastic Primal-Dual Hybrid Gradient.

Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher

SIAM J. Optim., 2022

Convergence and Complexity of Stochastic Subgradient Methods with Dependent Data for Nonconvex Optimization.

Ahmet Alacaoglu, Hanbaek Lyu

CoRR, 2022

On the Complexity of a Practical Primal-Dual Coordinate Method.

Ahmet Alacaoglu, Volkan Cevher, Stephen J. Wright

CoRR, 2022

A Natural Actor-Critic Framework for Zero-Sum Markov Games.

Ahmet Alacaoglu, Luca Viano, Niao He, Volkan Cevher

Proceedings of the International Conference on Machine Learning, 2022

Stochastic Variance Reduction for Variational Inequality Methods.

Ahmet Alacaoglu, Yura Malitsky

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond.

Ahmet Alacaoglu

PhD thesis, 2021

Forward-reflected-backward method with variance reduction.

Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

Comput. Optim. Appl., 2021

Convergence of adaptive algorithms for constrained weakly convex optimization.

Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

An adaptive primal-dual framework for nonsmooth convex minimization.

Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher

Math. Program. Comput., 2020

Convergence of adaptive algorithms for weakly convex constrained optimization.

Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher

CoRR, 2020

Conditional gradient methods for stochastically constrained convex minimization.

Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher

Proceedings of the 37th International Conference on Machine Learning, 2020

A new regret analysis for Adam-type algorithms.

Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher

Proceedings of the 37th International Conference on Machine Learning, 2020

Random extrapolation for primal-dual coordinate descent.

Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints.

Mehmet Fatih Sahin, Armin Eftekhari, Ahmet Alacaoglu, Fabian Latorre Gómez, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Almost surely constrained convex optimization.

Olivier Fercoq, Ahmet Alacaoglu, Ion Necoara, Volkan Cevher

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization.

Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017