2 citations · 2 across the 5 of their papers we have counts for
5 papers
madupite: A High-Performance Distributed Solver for Large-Scale Markov Decision Processes
Matilde Gargiani, Robin Sieber, Philip Pawlowsky +2
This paper introduces madupite, a high-performance distributed solver for large-scale Markov Decision Processes (MDPs). MDPs are widely used to model complex dynamical systems in v…
Secure Data Reconstruction: A Direct Data-Driven Approach
Jiaqi Yan, Ivan Markovsky, John Lygeros
This paper addresses the problem of secure data reconstruction for unknown systems, where data collected from the system are susceptible to malicious manipulation. We aim to recove…
Semismooth Newton Methods for Risk-Averse Markov Decision Processes
Matilde Gargiani, Francesco Micheli, Anastasios Tsiamis +1
Inspired by semismooth Newton methods, we propose a general framework for designing solution methods with convergence guarantees for risk-averse Markov decision processes. Our appr…
Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
Jialin Li, Marta Zagorowska, Giulia De Pasquale +2
Ensuring safety is a key aspect in sequential decision making problems, such as robotics or process control. The complexity of the underlying systems often makes finding the optima…
Online Residual Learning from Offline Experts for Pedestrian Tracking
Anastasios Vlachos, Anastasios Tsiamis, Aren Karapetyan +2
In this paper, we consider the problem of predicting unknown targets from data. We propose Online Residual Learning (ORL), a method that combines online adaptation with offline-tra…