Mehmet Fatih Sahin

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Mentions légales

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Publications associées (4)

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Sound and Complete Verification of Polynomial Networks

Volkan Cevher, Mehmet Fatih Sahin, Grigorios Chrysos, Fanghui Liu, Elias Abad Rocamora

Polynomial Networks (PNs) have demonstrated promising performance on face and image recognition recently. However, robustness of PNs is unclear and thus obtaining certificates becomes imperative for enabling their adoption in real-world applications. Exist ...

2022

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints

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

We propose a practical inexact augmented Lagrangian method (iALM) for nonconvex problems with nonlinear constraints. We characterize the total computational complexity of our method subject to a verifiable geometric condition, which is closely related to t ...

2019

Let’s be honest: An optimal no-regret framework for zero-sum games

Volkan Cevher, Ya-Ping Hsieh, Mehmet Fatih Sahin, Ehsan Asadi Kangarshahi

We revisit the problem of solving two-player zero- sum games in the decentralized setting. We pro- pose a simple algorithmic framework that simulta- neously achieves the best rates for honest regret as well as adversarial regret, and in addition resolves t ...

2018

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