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ORCIDNecdet Serhat Aybat
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- affiliation: Penn State, University Park, USA
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Journal Articles
- 2024
[j19]Omar M. Sleem
, Mahmoud E. Ashour, Necdet Serhat Aybat, Constantino M. Lagoa:
Lp quasi-norm minimization: algorithm and applications. EURASIP J. Adv. Signal Process. 2024(1): 22 (2024)- [j18]Xuan Zhang, Necdet Serhat Aybat, Mert Gürbüzbalaban:
Robust Accelerated Primal-Dual Methods for Computing Saddle Points. SIAM J. Optim. 34(1): 1097-1130 (2024) - [j17]Diyako Ghaderyan, Necdet Serhat Aybat, A. Pedro Aguiar, Fernando M. Lobo Pereira:
A Fast Row-Stochastic Decentralized Method for Distributed Optimization Over Directed Graphs. IEEE Trans. Autom. Control. 69(1): 275-289 (2024) - 2022
- [j16]Necdet Serhat Aybat, Hesam Ahmadi, Uday V. Shanbhag:
On the Analysis of Inexact Augmented Lagrangian Schemes for Misspecified Conic Convex Programs. IEEE Trans. Autom. Control. 67(8): 3981-3996 (2022) - [j15]Erfan Yazdandoost Hamedani, Necdet Serhat Aybat:
A Decentralized Primal-Dual Method for Constrained Minimization of a Strongly Convex Function. IEEE Trans. Autom. Control. 67(11): 5682-5697 (2022) - [j14]Bugra Can, Saeed Soori, Necdet Serhat Aybat, Maryam Mehri Dehnavi, Mert Gürbüzbalaban:
Randomized Gossiping With Effective Resistance Weights: Performance Guarantees and Applications. IEEE Trans. Control. Netw. Syst. 9(2): 524-536 (2022) - 2021
- [j13]Erfan Yazdandoost Hamedani, Necdet Serhat Aybat:
A Primal-Dual Algorithm with Line Search for General Convex-Concave Saddle Point Problems. SIAM J. Optim. 31(2): 1299-1329 (2021) - 2020
- [j12]Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar:
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions. SIAM J. Optim. 30(1): 717-751 (2020) - 2019
- [j11]Jingyao Wang, Mahmoud E. Ashour, Constantino M. Lagoa, Necdet Serhat Aybat, Hao Che:
A fully distributed traffic allocation algorithm for nonconcave utility maximization in connectionless communication networks. Autom. 109 (2019) - [j10]Necdet Serhat Aybat, Erfan Yazdandoost Hamedani:
A Distributed ADMM-like Method for Resource Sharing over Time-Varying Networks. SIAM J. Optim. 29(4): 3036-3068 (2019) - [j9]Mahmoud E. Ashour, Jingyao Wang, Necdet Serhat Aybat, Constantino Lagoa, Hao Che:
End-to-End Distributed Flow Control for Networks with Nonconcave Utilities. IEEE Trans. Netw. Sci. Eng. 6(3): 303-313 (2019) - 2018
- [j8]Shiqian Ma, Necdet Serhat Aybat:
Efficient Optimization Algorithms for Robust Principal Component Analysis and Its Variants. Proc. IEEE 106(8): 1411-1426 (2018) - [j7]Necdet Serhat Aybat, Zi Wang, Tianyi Lin, Shiqian Ma:
Distributed Linearized Alternating Direction Method of Multipliers for Composite Convex Consensus Optimization. IEEE Trans. Autom. Control. 63(1): 5-20 (2018) - 2015
- [j6]Necdet S. Aybat, Garud Iyengar:
An alternating direction method with increasing penalty for stable principal component pursuit. Comput. Optim. Appl. 61(3): 635-668 (2015) - [j5]Ashkan M. Jasour, Necdet S. Aybat, Constantino M. Lagoa:
Semidefinite Programming For Chance Constrained Optimization Over Semialgebraic Sets. SIAM J. Optim. 25(3): 1411-1440 (2015) - 2014
- [j4]Necdet Serhat Aybat, Donald Goldfarb, Shiqian Ma:
Efficient algorithms for robust and stable principal component pursuit problems. Comput. Optim. Appl. 58(1): 1-29 (2014) - [j3]Necdet S. Aybat, Garud Iyengar:
A unified approach for minimizing composite norms. Math. Program. 144(1-2): 181-226 (2014) - 2012
- [j2]Necdet S. Aybat, Garud Iyengar:
A First-Order Augmented Lagrangian Method for Compressed Sensing. SIAM J. Optim. 22(2): 429-459 (2012) - 2011
- [j1]Necdet S. Aybat, Garud Iyengar:
A First-Order Smoothed Penalty Method for Compressed Sensing. SIAM J. Optim. 21(1): 287-313 (2011)
Conference and Workshop Papers
- 2024
- [c16]Xuan Zhang, Gabriel Mancino-Ball, Necdet Serhat Aybat, Yangyang Xu:
Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization. AAAI 2024: 20865-20873 - 2023
- [c15]Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh, Necdet S. Aybat:
Randomized Primal-Dual Methods with Adaptive Step Sizes. AISTATS 2023: 11185-11212 - 2022
- [c14]Xuan Zhang, Necdet Serhat Aybat, Mert Gürbüzbalaban:
SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems. NeurIPS 2022 - 2019
- [c13]Mahmoud E. Ashour, Constantino M. Lagoa, Necdet S. Aybat:
Lp Quasi-norm Minimization. ACSSC 2019: 726-730 - [c12]Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar:
A Universally Optimal Multistage Accelerated Stochastic Gradient Method. NeurIPS 2019: 8523-8534 - 2017
- [c11]Erfan Yazdandoost Hamedani, Necdet Serhat Aybat:
Multi-agent constrained optimization of a strongly convex function over time-varying directed networks. Allerton 2017: 518-525 - [c10]Jingyao Wang, Mahmoud E. Ashour, Constantino Lagoa, Necdet S. Aybat, Hao Che, Zhisheng Duan:
Non-concave network utility maximization in connectionless networks: A fully distributed traffic allocation algorithm. ACC 2017: 3980-3985 - [c9]Necdet Serhat Aybat, Mert Gürbüzbalaban:
Decentralized computation of effective resistances and acceleration of consensus algorithms. GlobalSIP 2017: 538-542 - [c8]Erfan Yazdandoost Hamedani, Necdet Serhat Aybat:
Multi-agent constrained optimization of a strongly convex function. GlobalSIP 2017: 558-562 - [c7]Mahmoud E. Ashour, Jingyao Wang, Constantino Lagoa, Necdet Serhat Aybat, Hao Che:
Non-concave network utility maximization: A distributed optimization approach. INFOCOM 2017: 1-9 - 2016
- [c6]Necdet Serhat Aybat, Erfan Yazdandoost Hamedani:
Distributed primal-dual method for multi-agent sharing problem with conic constraints. ACSSC 2016: 777-782 - [c5]Hesam Ahmadi, Necdet Serhat Aybat, Uday V. Shanbhag:
On the rate analysis of inexact augmented Lagrangian schemes for convex optimization problems with misspecified constraints. ACC 2016: 4841-4846 - [c4]Necdet Serhat Aybat, Erfan Yazdandoost Hamedani:
A primal-dual method for conic constrained distributed optimization problems. NIPS 2016: 5050-5058 - 2015
- [c3]Necdet S. Aybat, Zi Wang, Garud Iyengar:
An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization. ICML 2015: 2454-2462 - [c2]Necdet Serhat Aybat, Sahar Zarmehri, Soundar R. T. Kumara:
An ADMM Algorithm for Clustering Partially Observed Networks. SDM 2015: 460-468 - 2014
- [c1]Necdet S. Aybat, Zi Wang:
A parallel method for large scale convex regression problems. CDC 2014: 5710-5717
Informal and Other Publications
- 2022
- [i5]Bugra Can, Mert Gürbüzbalaban, Necdet Serhat Aybat:
A Variance-Reduced Stochastic Accelerated Primal Dual Algorithm. CoRR abs/2202.09688 (2022) - 2021
- [i4]Diyako Ghaderyan, Necdet Serhat Aybat, A. Pedro Aguiar, Fernando M. Lobo Pereira:
A Fast Row-Stochastic Decentralized Optimization Method Over Directed Graphs. CoRR abs/2112.13257 (2021) - 2019
- [i3]Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar:
A Universally Optimal Multistage Accelerated Stochastic Gradient Method. CoRR abs/1901.08022 (2019) - 2018
- [i2]Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar:
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions. CoRR abs/1805.10579 (2018) - [i1]Shiqian Ma, Necdet Serhat Aybat:
Efficient Optimization Algorithms for Robust Principal Component Analysis and Its Variants. CoRR abs/1806.03430 (2018)
Coauthor Index
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