Zobrazeno 1 - 10
of 536
pro vyhledávání: '"Rikos, A."'
In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we
Externí odkaz:
http://arxiv.org/abs/2409.05418
In this paper we address distributed learning problems over peer-to-peer networks. In particular, we focus on the challenges of quantized communications, asynchrony, and stochastic gradients that arise in this set-up. We first discuss how to turn the
Externí odkaz:
http://arxiv.org/abs/2408.17156
Autor:
Talaei, Mahtab, Rikos, Apostolos I., Olshevsky, Alex, White, Laura F., Paschalidis, Ioannis Ch.
Motivated by the swift global transmission of infectious diseases, we present a comprehensive framework for network-based epidemic control. Our aim is to curb epidemics using two different approaches. In the first approach, we introduce an optimizati
Externí odkaz:
http://arxiv.org/abs/2407.19133
Autor:
Silano, Giuseppe, Rikos, Evangelos, Rajkumar, Vetrivel, Gehrke, Oliver, Zerihun, Tesfaye Amare, Rodio, Carmine, Lazzari, Riccardo
This paper investigates the integration and validation of multi-energy systems within the H2020 ERIGrid 2.0 project, focusing on the deployment of the JaNDER software middleware and universal API (uAPI) to establish a robust, high-data-rate, and low-
Externí odkaz:
http://arxiv.org/abs/2407.00093
In this paper, we present a novel distributed algorithm (herein called MaxCUCL) designed to guarantee that max-consensus is reached in networks characterized by unreliable communication links (i.e., links suffering from packet drops). Our proposed al
Externí odkaz:
http://arxiv.org/abs/2402.18719
Autor:
Doostmohammadian, Mohammadreza, Aghasi, Alireza, Pirani, Mohammad, Nekouei, Ehsan, Zarrabi, Houman, Keypour, Reza, Rikos, Apostolos I., Johansson, Karl H.
Resource allocation and scheduling in multi-agent systems present challenges due to complex interactions and decentralization. This survey paper provides a comprehensive analysis of distributed algorithms for addressing the distributed resource alloc
Externí odkaz:
http://arxiv.org/abs/2401.15607
In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence informat
Externí odkaz:
http://arxiv.org/abs/2309.04588
In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we
Externí odkaz:
http://arxiv.org/abs/2309.04585
In this paper we consider online distributed learning problems. Online distributed learning refers to the process of training learning models on distributed data sources. In our setting a set of agents need to cooperatively train a learning model fro
Externí odkaz:
http://arxiv.org/abs/2307.06620
Autor:
Rikos, Apostolos I., Grammenos, Andreas, Kalyvianaki, Evangelia, Hadjicostis, Christoforos N., Charalambous, Themistoklis, Johansson, Karl H.
We propose two distributed iterative algorithms that can be used to solve, in finite time, the distributed optimization problem over quadratic local cost functions in large-scale networks. The first algorithm exhibits synchronous operation whereas th
Externí odkaz:
http://arxiv.org/abs/2304.00596