Zobrazeno 1 - 10
of 890
pro vyhledávání: '"Johansson, Karl Henrik"'
This paper investigates the use of the cubic-regularized Newton method within a federated learning framework while addressing two major concerns that commonly arise in federated learning: privacy leakage and communication bottleneck. We introduce a f
Externí odkaz:
http://arxiv.org/abs/2408.04315
We introduce a real-time identification method for discrete-time state-dependent switching systems in both the input--output and state-space domains. In particular, we design a system of adaptive algorithms running in two timescales; a stochastic app
Externí odkaz:
http://arxiv.org/abs/2408.01730
Autor:
Mamaghan, Amir Mohammad Karimi, Papa, Samuele, Johansson, Karl Henrik, Bauer, Stefan, Dittadi, Andrea
Object-centric (OC) representations, which represent the state of a visual scene by modeling it as a composition of objects, have the potential to be used in various downstream tasks to achieve systematic compositional generalization and facilitate r
Externí odkaz:
http://arxiv.org/abs/2407.15589
In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks' nontrivial charging times and the stations' limited charging facilities. Our goal is
Externí odkaz:
http://arxiv.org/abs/2407.10307
Autor:
Mamaghan, Amir Mohammad Karimi, Tigas, Panagiotis, Johansson, Karl Henrik, Gal, Yarin, Annadani, Yashas, Bauer, Stefan
Representing uncertainty in causal discovery is a crucial component for experimental design, and more broadly, for safe and reliable causal decision making. Bayesian Causal Discovery (BCD) offers a principled approach to encapsulating this uncertaint
Externí odkaz:
http://arxiv.org/abs/2406.03209
This paper investigates privacy issues in distributed resource allocation over directed networks, where each agent holds a private cost function and optimizes its decision subject to a global coupling constraint through local interaction with other a
Externí odkaz:
http://arxiv.org/abs/2403.18275
A given region in 2-D Euclidean space is divided by a unknown linear classifier in to two sets each carrying a label. The objective of an agent with known dynamics traversing the region is to identify the true classifier while paying a control cost a
Externí odkaz:
http://arxiv.org/abs/2403.15687
Autor:
Chen, Guanpu, Xu, Gehui, He, Fengxiang, Tao, Dacheng, Parisini, Thomas, Johansson, Karl Henrik
In this note, we investigate the robustness of Nash equilibria (NE) in multi-player aggregative games with coupling constraints. There are many algorithms for computing an NE of an aggregative game given a known aggregator. When the coupling paramete
Externí odkaz:
http://arxiv.org/abs/2403.10980
We consider the problem of estimation of a function by a system consisting of two agents and a fusion center. The two agents collect data comprising of samples of an independent variable and the corresponding value of a dependent variable. The object
Externí odkaz:
http://arxiv.org/abs/2403.07749
We consider the problem of function estimation by a multi-agent system comprising of two agents and a fusion center. Each agent receives data comprising of samples of an independent variable (input) and the corresponding values of the dependent varia
Externí odkaz:
http://arxiv.org/abs/2401.03012