Compressed Federated Reinforcement Learning with a Generative Model

Author:

Beikmohammadi AliORCID,Khirirat SaritORCID,Magnússon SindriORCID

Publisher

Springer Nature Switzerland

Reference73 articles.

1. Alistarh, D., Grubic, D., Li, J., Tomioka, R., Vojnovic, M.: QSGD: communication-efficient SGD via gradient quantization and encoding. In: Advances in Neural Information Processing Systems, vol. 30 (2017)

2. Alistarh, D., Hoefler, T., Johansson, M., Konstantinov, N., Khirirat, S., Renggli, C.: The convergence of sparsified gradient methods. In: Advances in Neural Information Processing Systems, vol. 31 (2018)

3. Assran, M., Romoff, J., Ballas, N., Pineau, J., Rabbat, M.: Gossip-based actor-learner architectures for deep reinforcement learning. In: Advances in Neural Information Processing Systems, vol. 32 (2019)

4. Azar, M.G., Munos, R., Ghavamzadeh, M., Kappen, H.: Speedy Q-learning. In: Advances in Neural Information Processing Systems (2011)

5. Beck, C.L., Srikant, R.: Error bounds for constant step-size Q-learning. Syst. Control Lett. 61(12), 1203–1208 (2012)

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