Ahmet Alacaoglu (2021)

Research Interests:

  • Convex Optimization
  • Stochastic Optimization
  • Image Processing

 

Biographie

I received my BSc in Electrical and Electronics Engineering Department of Bilkent University, Ankara, Turkey, in 2016. In September the same year, I started my PhD thesis at EPFL, LIONS which I sucessfully defended in 2021. The thesis, entitled “Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond” was supervised by Prof. Volkan Cevher.

Publications (most recent)

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

A. Alacaoglu; L. Viano; N. He; V. Cevher 

2022. 39th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, July 17-23, 2022.

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

A. Alacaoglu; O. Fercoq; V. Cevher 

Siam Journal On Optimization. 2022-01-01. Vol. 32, num. 2, p. 1288-1318. DOI : 10.1137/19M1296252.

Forward-reflected-backward method with variance reduction

A. Alacaoglu; Y. Malitsky; V. Cevher 

Computational Optimization and Applications. 2021-08-19. Vol. 80, p. 321–346. DOI : 10.1007/s10589-021-00305-3.

Convergence of adaptive algorithms for constrained weakly convex optimization

A. Alacaoglu; Y. Malitskyi; V. Cevher 

2021. 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 6-14, 2021.

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

A. Alacaoglu / V. Cevher (Dir.)  

Lausanne, EPFL, 2021. 

Random extrapolation for primal-dual coordinate descent

A. Alacaoglu; O. Fercoq; V. Cevher 

2020. 37th International Conference on Machine Learning (ICML 2020), Online, July 13-18, 2020.

Conditional gradient methods for stochastically constrained convex minimization

M-L. Vladarean; A. Alacaoglu; Y-P. Hsieh; V. Cevher 

2020. 37th International Conference on Machine Learning (ICML), virtual, July 12-18, 2020.

A new regret analysis for Adam-type algorithms

A. Alacaoglu; Y. Malitsky; P. Mertikopoulos; V. Cevher 

2020. 37th International Conference on Machine Learning (ICLM 2020), Virtual, July 13-18, 2020.

An adaptive primal-dual framework for nonsmooth convex minimization

Q. Tran-Dinh; A. Alacaoglu; O. Fercoq; V. Cevher 

Mathematical Programming Computation. 2020. Vol. 12, p. 451–491. DOI : 10.1007/s12532-019-00173-3.

On the convergence of stochastic primal-dual hybrid gradient

A. Alacaoglu; O. Fercoq; V. Cevher 

2019

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints

M. F. Sahin; A. Eftekhari; A. Alacaoglu; F. R. Latorre Gomez; V. Cevher 

2019. NeurIPS 2019 : Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, December 8-14, 2019.

Almost surely constrained convex optimization

O. Fercoq; A. Alacaoglu; I. Necoara; V. Cevher 

2019. 36th International Conference on Machine Learning (ICML 2019), Long Beach, USA, June 9-15, 2019.

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

A. Alacaoglu; Q. Tran-Dinh; O. Fercoq; V. Cevher 

2017. 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA, December 4-9, 2017.