Search Results for author: Ceyhun Eksin

Found 5 papers, 2 papers with code

Learning graph-Fourier spectra of textured surface images for defect localization

no code implementations25 Nov 2023 Tapan Ganatma Nakkina, Adithyaa Karthikeyan, Yuhao Zhong, Ceyhun Eksin, Satish T. S. Bukkapatnam

This paper introduces an approach based on graph Fourier analysis to automatically identify defective images, as well as crucial graph Fourier coefficients that inform the defects in images amidst highly textured backgrounds.

Maximizing Social Welfare and Agreement via Information Design in Linear-Quadratic-Gaussian Games

1 code implementation25 Feb 2021 Furkan Sezer, Hossein Khazaei, Ceyhun Eksin

We show that full information disclosure maximizes social welfare when there is a common payoff-relevant state, when there is strategic substitutability in the actions of players, or when the signals are public.

Optimization and Control Multiagent Systems Systems and Control General Economics Systems and Control Economics

A Best-Response Algorithm with Voluntary Communication and Mobility Protocols for Mobile Autonomous Teams Solving the Target Assignment Problem

1 code implementation6 Mar 2020 Sarper Aydin, Ceyhun Eksin

Numerical simulations and experiments using a team of mobile robots confirm the target coverage in finite time and show that mobility control for communication and learning-aware voluntary communication protocols reduce the number of communication attempts in comparison to a benchmark distributed algorithm that relies on communication after every decision epoch.

Optimal evolutionary control for artificial selection on molecular phenotypes

no code implementations31 Dec 2019 Armita Nourmohammad, Ceyhun Eksin

Controlling an evolving population is an important task in modern molecular genetics, including directed evolution for improving the activity of molecules and enzymes, in breeding experiments in animals and in plants, and in devising public health strategies to suppress evolving pathogens.

Distributed Networked Learning with Correlated Data

no code implementations28 Oct 2019 Lingzhou Hong, Alfredo Garcia, Ceyhun Eksin

We consider a distributed estimation method in a setting with heterogeneous streams of correlated data distributed across nodes in a network.

Federated Learning

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