Robust Value Function Approximation by Working Backwards [PDF]
, 1995 In this paper, we examine the intuition that TD() is meant to operate by approximating asynchronous value iteration. We note that on the important class of discrete acyclic stochastic tasks, value iteration is inefficient compared with the DAG-SP ...
Andrew W. Moore, Justin A. Boyan
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Distributed stochastic gradient descent (SGD) has attracted considerable recent attention due to its potential for scaling computational resources, reducing training time, and helping protect user privacy in machine learning.
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