In compressed decentralized optimization settings, there are benefits to having multiple gossip steps between subsequent gradient iterations, even when the cost of doing so is appropriately accounted for e.g. by means of reducing the precision of compressed information.
License: MIT License
Hello, I am trying to modify the simulation to use stochastic gradient descent (SGD) instead of gradient descent (GD). However, it appears that the result is not as expected, with the loss value continuously increasing.
What could be the underlying reason for this phenomenon?
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