Adrian Redder

aredder@mail.uni-paderborn.de
ID
52265

8 Publications

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[8]
2023 | Book Chapter | LibreCat-ID: 45895 | OA
Karl, H., Maack, M., Meyer auf der Heide, F., Pukrop, S., & Redder, A. (2023). On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 183–202). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068664
LibreCat | Files available | DOI
 
[7]
2022 | Conference Paper | LibreCat-ID: 32811
Redder, A., Ramaswamy, A., & Karl, H. (2022). Age of Information Process under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law. Proceedings of the 58th Allerton Conference on Communication, Control, and Computing. 58th Allerton Conference on Communication, Control, and Computing.
LibreCat
 
[6]
2022 | Conference Paper | LibreCat-ID: 30793
Redder, A., Ramaswamy, A., & Karl, H. (2022). Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy Communication. Proceedings of the 14th International Conference on Agents and Artificial Intelligence. https://doi.org/10.5220/0010845400003116
LibreCat | Files available | DOI
 
[5]
2022 | Preprint | LibreCat-ID: 30790
Redder, A., Ramaswamy, A., & Karl, H. (2022). Distributed gradient-based optimization in the presence of dependent  aperiodic communication. In arXiv:2201.11343.
LibreCat | arXiv
 
[4]
2022 | Preprint | LibreCat-ID: 30791
Redder, A., Ramaswamy, A., & Karl, H. (2022). Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms. In arXiv:2201.00570.
LibreCat | arXiv
 
[3]
2022 | Journal Article | LibreCat-ID: 32854
Redder, A., Ramaswamy, A., & Karl, H. (2022). Practical Network Conditions for the Convergence of Distributed Optimization. IFAC-PapersOnLine, 55(13), 133–138.
LibreCat | Files available
 
[2]
2021 | Journal Article | LibreCat-ID: 24140
Ramaswamy, A., Redder, A., & Quevedo, D. E. (2021). Distributed optimization over time-varying networks with stochastic information delays. IEEE Transactions on Automatic Control, 1–1. https://doi.org/10.1109/TAC.2021.3108492
LibreCat | DOI
 
[1]
2019 | Conference Paper | LibreCat-ID: 13443 | OA
Redder, A., Ramaswamy, A., & Quevedo, D. (2019). Deep reinforcement learning for scheduling in large-scale networked control systems. In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems. Chicago, USA.
LibreCat | Files available | Download (ext.)
 
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8 Publications

Mark all

[8]
2023 | Book Chapter | LibreCat-ID: 45895 | OA
Karl, H., Maack, M., Meyer auf der Heide, F., Pukrop, S., & Redder, A. (2023). On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 183–202). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068664
LibreCat | Files available | DOI
 
[7]
2022 | Conference Paper | LibreCat-ID: 32811
Redder, A., Ramaswamy, A., & Karl, H. (2022). Age of Information Process under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law. Proceedings of the 58th Allerton Conference on Communication, Control, and Computing. 58th Allerton Conference on Communication, Control, and Computing.
LibreCat
 
[6]
2022 | Conference Paper | LibreCat-ID: 30793
Redder, A., Ramaswamy, A., & Karl, H. (2022). Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy Communication. Proceedings of the 14th International Conference on Agents and Artificial Intelligence. https://doi.org/10.5220/0010845400003116
LibreCat | Files available | DOI
 
[5]
2022 | Preprint | LibreCat-ID: 30790
Redder, A., Ramaswamy, A., & Karl, H. (2022). Distributed gradient-based optimization in the presence of dependent  aperiodic communication. In arXiv:2201.11343.
LibreCat | arXiv
 
[4]
2022 | Preprint | LibreCat-ID: 30791
Redder, A., Ramaswamy, A., & Karl, H. (2022). Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms. In arXiv:2201.00570.
LibreCat | arXiv
 
[3]
2022 | Journal Article | LibreCat-ID: 32854
Redder, A., Ramaswamy, A., & Karl, H. (2022). Practical Network Conditions for the Convergence of Distributed Optimization. IFAC-PapersOnLine, 55(13), 133–138.
LibreCat | Files available
 
[2]
2021 | Journal Article | LibreCat-ID: 24140
Ramaswamy, A., Redder, A., & Quevedo, D. E. (2021). Distributed optimization over time-varying networks with stochastic information delays. IEEE Transactions on Automatic Control, 1–1. https://doi.org/10.1109/TAC.2021.3108492
LibreCat | DOI
 
[1]
2019 | Conference Paper | LibreCat-ID: 13443 | OA
Redder, A., Ramaswamy, A., & Quevedo, D. (2019). Deep reinforcement learning for scheduling in large-scale networked control systems. In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems. Chicago, USA.
LibreCat | Files available | Download (ext.)
 
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