Ahmet Alacaoglu

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 27

Top Topics

Linear Programming

Convex Optimization

Interior Point Methods

Top Venues

Publications

Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions. ICLR (2024)
Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright
Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity. CoRR (2024)
Ahmet Alacaoglu, Stephen J. Wright
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints. AISTATS (2024)
Ahmet Alacaoglu, Hanbaek Lyu
Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data. ICML (2023)
Ahmet Alacaoglu, Stephen J. Wright
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints. CoRR (2023)
Ahmet Alacaoglu, Axel Böhm, Yura Malitsky
Beyond the Golden Ratio for Variational Inequality Algorithms. J. Mach. Learn. Res. 24 (2023)
Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions. CoRR (2023)
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
On the Convergence of Stochastic Primal-Dual Hybrid Gradient. SIAM J. Optim. 32 (2) (2022)
Ahmet Alacaoglu, Luca Viano, Niao He, Volkan Cevher
A Natural Actor-Critic Framework for Zero-Sum Markov Games. ICML (2022)
Ahmet Alacaoglu, Volkan Cevher, Stephen J. Wright
On the Complexity of a Practical Primal-Dual Coordinate Method. CoRR (2022)
Ahmet Alacaoglu, Yura Malitsky
Stochastic Variance Reduction for Variational Inequality Methods. COLT (2022)
Ahmet Alacaoglu, Hanbaek Lyu
Convergence and Complexity of Stochastic Subgradient Methods with Dependent Data for Nonconvex Optimization. CoRR (2022)
Ahmet Alacaoglu, Axel Böhm, Yura Malitsky
Beyond the Golden Ratio for Variational Inequality Algorithms. CoRR (2022)
Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
Convergence of adaptive algorithms for constrained weakly convex optimization. NeurIPS (2021)
Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
Forward-reflected-backward method with variance reduction. Comput. Optim. Appl. 80 (2) (2021)
Ahmet Alacaoglu, Yura Malitsky
Stochastic Variance Reduction for Variational Inequality Methods. CoRR (2021)
Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher
A new regret analysis for Adam-type algorithms. CoRR (2020)
Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher
Conditional gradient methods for stochastically constrained convex minimization. CoRR (2020)
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
Random extrapolation for primal-dual coordinate descent. ICML (2020)
Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
Convergence of adaptive algorithms for weakly convex constrained optimization. CoRR (2020)
Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
An adaptive primal-dual framework for nonsmooth convex minimization. Math. Program. Comput. 12 (3) (2020)
Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher
A new regret analysis for Adam-type algorithms. ICML (2020)
Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher
Conditional gradient methods for stochastically constrained convex minimization. ICML (2020)
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
Random extrapolation for primal-dual coordinate descent. CoRR (2020)
Olivier Fercoq, Ahmet Alacaoglu, Ion Necoara, Volkan Cevher
Almost surely constrained convex optimization. ICML (2019)
Mehmet Fatih Sahin, Armin Eftekhari, Ahmet Alacaoglu, Fabian Latorre Gómez, Volkan Cevher
An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints. NeurIPS (2019)
Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization. NIPS (2017)