| Towards encrypted MPC for linear constrained systems MS Darup, A Redder, I Shames, F Farokhi, D Quevedo IEEE Control Systems Letters 2 (2), 195-200, 2017 | 125 | 2017 |
| Encrypted cooperative control based on structured feedback MS Darup, A Redder, DE Quevedo IEEE control systems letters 3 (1), 37-42, 2018 | 71 | 2018 |
| Encrypted cloud-based MPC for linear systems with input constraints MS Darup, A Redder, DE Quevedo IFAC-PapersOnLine 51 (20), 535-542, 2018 | 54 | 2018 |
| On the use of artificial noise for secure state estimation in the presence of eavesdroppers AS Leong, A Redder, DE Quevedo, S Dey 2018 European Control Conference (ECC), 325-330, 2018 | 21 | 2018 |
| Deep reinforcement learning for scheduling in large-scale networked control systems A Redder, A Ramaswamy, DE Quevedo IFAC-PapersOnLine 52 (20), 333-338, 2019 | 18 | 2019 |
| Asymptotic convergence of deep multi-agent actor-critic algorithms A Redder, A Ramaswamy, H Karl arXiv: 2201.00570, 2022 | 11 | 2022 |
| Optimization over time-varying networks and unbounded information delays A Ramaswamy, A Redder, DE Quevedo IEEE Transactions on Automatic Control 67 (8), 4131-4137, 2021 | 10* | 2021 |
| Age of information process under strongly mixing communication-moment bound, mixing rate and strong law A Redder, A Ramaswamy, H Karl 2022 58th Annual Allerton Conference on Communication, Control, and …, 2022 | 6 | 2022 |
| Practical network conditions for the convergence of distributed optimization A Redder, A Ramaswamy, H Karl IFAC-PapersOnLine 55 (13), 133-138, 2022 | 5 | 2022 |
| 3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems A Redder, A Ramaswamy, H Karl arXiv preprint: arXiv:2201.00570v2, 2022 | 4 | 2022 |
| Machine Learning with Computer Networks: Techniques, Datasets and Models H Afifi, S Pochaba, A Boltres, D Laniewski, J Haberer, P Leonard, ... IEEE access, 2024 | 3 | 2024 |
| Stability and Convergence of Distributed Stochastic Approximations with large Unbounded Stochastic Information Delays A Redder, A Ramaswamy, H Karl arXiv preprint arXiv:2305.07091, 2023 | 2 | 2023 |
| Distributed gradient-based optimization in the presence of dependent aperiodic communication A Redder, A Ramaswamy, H Karl arXiv preprint arXiv:2201.11343, 2022 | 1 | 2022 |
| Machine Learning With Computer Networks: Techniques, Datasets, and Models N WEHNER, A REDDER, E SAMIKWA | | 2024 |
| Age-of-Information in Distributed Systems caused by Asynchronous Computing Modeled as Parallel Renewal Processes A Redder https://doi.org/10.21203/rs.3.rs-3502945/v2, 2023 | | 2023 |
| Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy Communication. A Redder, A Ramaswamy, H Karl ICAART (1), 282-289, 2022 | | 2022 |
| Practical sufficient conditions for convergence of distributed optimisation algorithms over communication networks with interference A Redder, A Ramaswamy, H Karl arXiv preprint arXiv:2105.04230, 2021 | | 2021 |
| A fixed-point implementation of explicit MPC laws MS Darup, A Redder, D Quevedo 2018 Annual American Control Conference (ACC), 749-755, 2018 | | 2018 |
| Lyapunov-Inspired Deep Reinforcement Learning for Robot Navigation in Obstacle Environments E Kayacan, HI Ugurlu, A Redder Available at SSRN 4858689, 0 | | |
| Subproject C4: On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers H Karl, M Maack, FM auf der Heide, S Pukrop, A Redder | | |
Daniel E. QuevedoQueensland University of Technology在 qut.edu.au 的电子邮件经过验证
