Batch-Expansion Training: An Efficient Optimization Framework

AISTATS, pp. 736-744, 2018.

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Abstract:

We propose Batch-Expansion Training (BET), a framework for running a batch optimizer on a gradually expanding dataset. As opposed to stochastic approaches, batches do not need to be resampled i.i.d. at every iteration, thus making BET more resource efficient in a distributed setting, and when disk-access is constrained. Moreover, BET can ...More

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