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Unit Tests for Stochastic Optimization
[article]
2014
arXiv
pre-print
Optimization by stochastic gradient descent is an important component of many large-scale machine learning algorithms. A wide variety of such optimization algorithms have been devised; however, it is unclear whether these algorithms are robust and widely applicable across many different optimization landscapes. In this paper we develop a collection of unit tests for stochastic optimization. Each unit test rapidly evaluates an optimization algorithm on a small-scale, isolated, and
arXiv:1312.6055v3
fatcat:5zkjnyuttrh2ros32ghpf4hrfe