• Corpus ID: 244773098

Adaptive Optimization with Examplewise Gradients

  title={Adaptive Optimization with Examplewise Gradients},
  author={Julius Kunze and James Townsend and David Barber},
We propose a new, more general approach to the design of stochastic gradient-based optimization methods for machine learning. In this new framework, optimizers assume access to a batch of gradient estimates per iteration, rather than a single estimate. This better reflects the information that is actually available in typical machine learning setups. To demonstrate the usefulness of this generalized approach, we develop Eve, an adaptation of the Adam optimizer which uses examplewise gradients… 

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