Publications
We like to inspire and share interesting knowledge!
- H Hellström, JMB da Silva Jr, MM Amiri, M Chen, V Fodor, HV Poor, C.Fischione, Wireless for Machine Learning: A Survey Foundations and Trends® in Signal Processing 15 (4), 290-39922022
- DP Souza, R Du, B da Silva Jr, J Mairton, CC Cavalcante, C Fischione, Leakage Detection In Water Distribution Networks: Efficient Training By Data Clustering, IWA World Water Congress & Exhibition 2022
- P Park, P Di Marco, C Fischione, Optimized over-the-air computation for wireless control systems, IEEE Communications Letters 26 (2), 2022
- H Hellström, V Fodor, C Fischione, Over-the-Air Federated Learning with Retransmissions, 2021 IEEE 22nd International Workshop on Signal Processing Advances in Communications
- JMB da Silva, K Ntougias, I Krikidis, G Fodor, C Fischione, Simultaneous Wireless Information and Power Transfer for Federated Learning, 2021 IEEE 22nd International Workshop on Signal Processing Advances in Communications
- P Park, P Di Marco, C Fischione, Wireless for control: Over-the-air controller, IEEE Communications Letters 25 (10), 3437-34411, 2021
- R Du, TO Timoudas, C Fischione, Comparing backscatter communication and energy harvesting in massive IoT networks, IEEE Transactions on Wireless Communications 21 (1), 429-4431, 2021
- P Park, HS Ghadikolaei, C Fischione, Proactive fault-tolerant wireless mesh networks for mission-critical control systems, Journal of Network and Computer Applications 186, 1030824, 2021
- Y Kim, E Al Hakim, J Haraldson, H Eriksson, JMB da Silva, C Fischione, Dynamic clustering in federated learning, ICC 2021-IEEE International Conference on Communications, 1-610, 2021
- R Du, S Magnusson, C Fischione, The Internet of Things as a deep neural network, IEEE Communications Magazine 58 (9), 20-2511, 2020
- R Du, S Magnússon, C Fischione, The IoT as a Deep Neural Network, IEEE Communications Magazine, 2, 2020
- TO Timoudas, R Du, C Fischione, Enabling massive IoT in ambient backscatter communication systems, ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-64 2020
- A Mahmoudi, HS Ghadikolaei, C Fischione, Cost-efficient distributed optimization in machine learning over wireless networks, ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-77, 2020
- A Mahmoudi, HS Ghadikolaei, C Fischione, Machine learning over networks: co-design of distributed optimization and communications, 2020 IEEE 21st International Workshop on Signal Processing Advances in Communications
- M. Zeng, V. Fodor, Energy minimization for delay constrained mobile edge computing with orthogonal and non-orthogonal multiple access, Ad Hoc Networks, Vol. 98, 2020.
- M. Zeng and V. Fodor, “Parallel Processing at the Edge in Dense Wireless Networks,” in IEEE Open Journal of the Communications Society, vol. 3, 2022
- J. A. Peris and V. Fodor, “Modelling multi-cell edge video analytics,” ICC 2022 – IEEE International Conference on Communications, 2022
- J. A. Peris and V. Fodor, “Distributed Join-the-Shortest-Queue with Sparse and Unreliable Information Updates,” ICC 2022 – IEEE International Conference on Communications, 2022
- J. A. Peris and V. Fodor, “Resource Dimensioning for Single-Cell Edge Video Analytics”, Swedish National Computer Networking Workshop, SNCNW, 2022.
- H. Hellström, V. Fodor and C. Fischione, “Over-the-Air Federated Learning with Retransmissions,” IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2021
- H. Hellström, V. Fodor, C. Fischione, “Unbiased Over-the-Air Computation via Retransmissions,” IEEE , Global Communications Conference (GLOBECOM), 2022.
- H. Hellström, V. Fodor, C. Fischione, “Bias Minimization for Over-the-Air Computation,” Swedish National Computer Networking Workshop, SNCNW, 2022.
- X. Wang, F. S. Samani, and R. Stadler, “Online feature selection for rapid, low-overhead learning in networked systems,” 16th International Conference on Network and Service Management (CNSM 2020). IEEE, 2020.
- R. S. Villaca and R. Stadler, “Online learning under resources constraints,” in 2021 17th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2021). IEEE, 2021.
- X. Wang, FS. Samani, A. Johnsson,R. Stadler, “Online Feature Selection for Low-overhead Learning in Networked Systems (Demonstration),” In 2021 17th International Conference on Network and Service Management (CNSM) 2021 Oct 25 (pp. 527-529). IEEE, 2021.
- X. Wang, R. Stadler, “Online Feature Selection for Efficient Learning in Networked System,” IEEE Transactions on Network and Service Management. 2022 Jun 8.
- L. Lindström, S. Gracy, S. Magnússon and H. Sandberg, “Leakage Localization in Water Distribution Networks: A Model-Based Approach”, European Control Conference, 2022
- A. Alanwar, A. Berndt, K.H. Johansson and H. Sandberg, “Data-Driven Set-Based Estimation Using Matrix Zonotopes with Set Containment Guarantees”, European Control Conference, 2022
- X. Wu, S. Magnússon, H. Reza Feyzmahdavian, M. Johansson, “Optimal convergence rates of totally asynchronous optimization”, IEEE Conference on Decision and Control (CDC), 2022
- M, Zhang, Q. Xu, S Magnússon, R. Pilawa-Podgurski and G. Guo, “Multi-Agent Deep Reinforcement Learning for Decentralized Voltage-Var Control in Distribution Power System”, IEEE Energy Conversion Congress and Exposition, 2022
- X. Wu, S. Magnússon, H. Reza Feyzmahdavian, and M. Johansson, “Delay-adaptive step-sizes for asynchronous learning” International Conference on Machine Learning (ICML), 2022
- I. Haasler, A. Ringh, Y. Chen, J. Karlsson, “Multi-marginal optimal transport with a tree-structured cost and the Schroedinger bridge problem,” SIAM Journal on Control and Optimization, 59(4), 2428-2453, 2021.
- I. Haasler, J. Karlsson, and A. Ringh, “Control and estimation of ensembles via structured optimal transport, A computational approach based on entropy-regularized multi-marginal optimal transport,” IEEE Control Systems Magazine 41 (4), 50-69, 2021.
- I. Haasler, A. Ringh, Y. Chen, and J. Karlsson, “Efficient computations of multi-species mean field games via graph-structured optimal transport,” IEEE Conference on Decision and Control, 2021.
- J. Fan, I. Haasler, J. Karlsson, and Y. Chen, “On the complexity of the optimal transport problem with graph-structured cost,” AISTATS, 2022.
- B. Ahlgren, and K-J Grinnemo, “ZQTRTT: a multipath scheduler for heterogeneous traffic in ICNs based on zero queueing time ratio”, In Proceedings of the 9th ACM Conference on Information-Centric Networking (ICN ’22), 2022.