1 citations · 1 across the 4 of their papers we have counts for
5 papers
Cross-Learning from Scarce Data via Multi-Task Constrained Optimization
Leopoldo Agorio, Juan Cerviño, Miguel Calvo-Fullana +2
A learning task, understood as the problem of fitting a parametric model from supervised data, fundamentally requires the dataset to be large enough to be representative of the und…
Cooperative Multi-Agent Assignment over Stochastic Graphs via Constrained Reinforcement Learning
Leopoldo Agorio, Sean Van Alen, Santiago Paternain +2
Constrained multi-agent reinforcement learning offers the framework to design scalable and almost surely feasible solutions for teams of agents operating in dynamic environments to…
Convolutional Filtering with RKHS Algebras
Alejandro Parada-Mayorga, Leopoldo Agorio, Alejandro Ribeiro +1
In this paper, we develop a generalized theory of convolutional signal processing and neural networks for Reproducing Kernel Hilbert Spaces (RKHS). Leveraging the theory of algebra…
Multi-agent assignment via state augmented reinforcement learning
Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana +2
We address the conflicting requirements of a multi-agent assignment problem through constrained reinforcement learning, emphasizing the inadequacy of standard regularization techni…
A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand
Miguel Calvo-Fullana, Mikhail Gerasimenko, Daniel Mox +5
Despite the prevalence of wireless connectivity in urban areas around the globe, there remain numerous and diverse situations where connectivity is insufficient or unavailable. To…