3 citations · 10 across the 23 of their papers we have counts for
8 papers · 1 filter
Online Optimization for Controlling HVAC Systems
Tong Wu, Dominik Baumann, Angela Fontan +1
Heating, ventilation, and air-conditioning (HVAC) systems account for a significant portion of buildings' energy consumption, motivating the design of energy- and cost-efficient co…
Distributed Grid Search for Hyperparameter Tuning
Constança De Herdeiro Cachim, Andrea Martin, Nicola Bastianello
The performance of many distributed optimization algorithms over peer-to-peer networks strongly depends on the choice of their hyperparameters. However, existing selection rules of…
Adaptive Online Optimization for Microgrids with Renewable Energy Sources
Wouter J. A. van Weerelt, Angela Fontan, Nicola Bastianello
In this paper we propose a novel adaptive online optimization algorithm tailored to the management of microgrids with high renewable energy penetration, which can be formulated as…
Self-Identifying Internal Model-Based Online Optimization
Wouter J. A. van Weerelt, Lantian Zhang, Silun Zhang +1
In this paper, we propose a novel online optimization algorithm built by combining ideas from control theory and system identification. The foundation of our algorithm is a control…
Control-Based Online Distributed Optimization
Wouter J. A. van Weerelt, Nicola Bastianello
In this paper we design a novel class of online distributed optimization algorithms leveraging control theoretical techniques. We start by focusing on quadratic costs, and assuming…
Optimization and Learning in Open Multi-Agent Systems
Diego Deplano, Nicola Bastianello, Mauro Franceschelli +1
Modern artificial intelligence relies on networks of agents that collect data, process information, and exchange it with neighbors to collaboratively solve optimization and learnin…
Asynchronous Distributed Learning with Quantized Finite-Time Coordination
Nicola Bastianello, Apostolos I. Rikos, Karl H. Johansson
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…
Learning Maximal Regions of Attraction on Compact Sets using Taylor Lyapunov Networks
Matthieu Barreau, Nicola Bastianello
We consider the problem of learning maximal Lyapunov functions to compute the maximal region of attraction of nonlinear dynamical systems using neural networks. Two obstacles limit…