Questions tagged [distributed-computing]

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How is the parameterised server updated in distributed DQN?

In this paper about Massively Parallel Methods for Deep Reinforcement Learning, the parallelisation of DQN is done via separating the actors and learners. Multiple actors carry out the $\epsilon$ ...
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Do I need to maintain a separate population in each distributed environment when implementing PBT in a MARL context?

I have questions regarding on how to implement PBT as described in Algorithm 1 (on page 5) in the paper, Population Based Training of Neural Networks to train agents in a MARL (multi-agent ...
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Why do we average gradients and not loss in distributed training?

I'm running some distributed trainings in Tensorflow with Horovod. It runs training separately on multiple workers, each of which uses the same weights and does forward pass on unique data. Computed ...
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In how few updates can a multi layer neural net be trained?

A single iteration of gradient descent can be parallelised across many worker nodes. We simple split the training set across the worker nodes, pass the parameters to each worker, each worker computes ...
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Artificial intelligence services at the edge

I am a strategy consultant, deeply interested in edge computing and distributed and decentralized systems. In performing some analysis on current edge offerings, I am curious as to how ML and AI ...