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Statistical curriculum learning: An elimination algorithm achieving an oracle risk
Feb. 22, 2024, 5:41 a.m. | Omer Cohen, Ron Meir, Nir Weinberger
cs.LG updates on arXiv.org arxiv.org
Abstract: We consider a statistical version of curriculum learning (CL) in a parametric prediction setting. The learner is required to estimate a target parameter vector, and can adaptively collect samples from either the target model, or other source models that are similar to the target model, but less noisy. We consider three types of learners, depending on the level of side-information they receive. The first two, referred to as strong/weak-oracle learners, receive high/low degrees of information …
abstract algorithm arxiv cs.lg curriculum curriculum learning oracle parametric prediction risk samples statistical stat.ml type vector
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