A. Alacaoglu, D. Kim and S. J. Wright, "Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity", arXiv:2402.05071, 2024

A. Alacaoglu, V. Cevher and S. J. Wright, "On the Complexity of a Practical Primal-Dual Coordinate Method", arXiv:2201.07684, 2022

X. Cai, A. Alacaoglu, J. Diakonikolas, "Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions",

*International Conference on Learning Representations (ICLR)*, 2024A. Alacaoglu and S. J. Wright, "Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints",

*International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2024A. Alacaoglu, A. Bohm and Y. Malitsky, "Beyond the Golden Ratio for Variational Inequality Algorithms",

*Journal of Machine Learning Research (JMLR)*, 2023A. Alacaoglu, H. Lyu, "Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data",

*International Conference on Machine Learning (ICML)*, 2023A. Alacaoglu, Y. Malitsky. "Stochastic Variance Reduction for Variational Inequality Methods",

*Conference on Learning Theory (COLT)*, 2022A. Alacaoglu, O. Fercoq, V. Cevher. "On the Convergence of Stochastic Primal-Dual Hybrid Gradient",

*SIAM Journal on Optimization (SIOPT)*, 2022A. Alacaoglu, L. Viano, N. He, V. Cevher. "A Natural Actor-Critic Framework for Zero-Sum Markov Games",

*International Conference on Machine Learning (ICML)*, 2022A. Alacaoglu, Y. Malitsky, V. Cevher. "Convergence of Adaptive Algorithms for Constrained Weakly Convex Optimization",

*Advances in Neural Information Processing Systems (NeurIPS)*, 2021A. Alacaoglu, Y. Malitsky, V. Cevher. "Forward-Reflected-Backward Method with Variance Reduction",

*Computational Optimization and Applications (COAP)*, 2021A. Alacaoglu, O. Fercoq, V. Cevher. "Random Extrapolation for Primal-Dual Coordinate Descent",

*International Conference on Machine Learning (ICML)*, 2020A. Alacaoglu, Y. Malitsky, P. Mertikopoulos, V. Cevher. "A New Regret Analysis for Adam-type Algorithms",

*International Conference on Machine Learning (ICML)*, 2020M.-L. Vladarean, A. Alacaoglu, Y.-P. Hsieh, V. Cevher. "Conditional gradient methods for stochastically constrained convex minimization",

*International Conference on Machine Learning (ICML)*, 2020M. F. Sahin, A. Eftekhari, A. Alacaoglu, F. Latorre, V. Cevher. "An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints",

*Advances in Neural Information Processing Systems (NeurIPS)*, 2019O. Fercoq, A. Alacaoglu, I. Necoara, V. Cevher. "Almost Surely Constrained Convex Optimization",

*International Conference on Machine Learning (ICML)*, 2019Q. Tran-Dinh, A. Alacaoglu, O. Fercoq, V. Cevher. "An Adaptive Primal-Dual Framework for Nonsmooth Convex Minimization",

*Mathematical Programming Computation*, 2019A. A. Ozaslan, A. Alacaoglu, O. B. Demirel, T. Cukur, E. U. Saritas. "Fully Automated Gridding Reconstruction for Non-Cartesian X-space Magnetic Particle Imaging",

*Physics in Medicine & Biology*, 2019A. Alacaoglu, Q. Tran-Dinh, O. Fercoq, V. Cevher. "Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization",

*Advances in Neural Information Processing Systems (NeurIPS)*, 2017