Co-Learning: Consensus-based Learning for Multi-Agent Systems

Author:

Carrascosa C.,Rincón J.,Rebollo M.

Publisher

Springer International Publishing

Reference13 articles.

1. McMahan, B., Moore, E., Ramage, D., Hampson, S., y Arcas, B.A.: Communication-efficient learning of deep networks from decentralized data. In: Artificial intelligence and statistics, pp. 1273–1282. PMLR (2017)

2. Kairouz, P., et al.: Advances and open problems in federated learning. Found. Trends ML 14(1–2), 1–210 (2021)

3. Olfati-Saber, R., Murray, R.M.: Consensus problems in networks of agents with switching topology and time-delays. IEEE TAC 49(9), 1520–1533 (2004)

4. Palanca, J., Terrasa, A., Julian, V., Carrascosa, C.: Spade 3: supporting the new generation of multi-agent systems. IEEE Access 8, 182537–182549 (2020)

5. Savazzi, S., Nicoli, M., Rampa, V.: Federated learning with cooperating devices: a consensus approach for massive IoT networks. IEEE Internet Things J. 7(5), 4641–4654 (2020)

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