2015 AdamAMethodforStochasticOptimiz

• (Kingma & Ba, 2015) ⇒ Diederik P. Kingma, and Jimmy Ba. (2015). “Adam: A Method for Stochastic Optimization.” In: Proceedings of the 3rd International Conference for Learning Representations (ICLR-2015).

Subject Headings: Adam Optimization Algorithm; First-Order Gradient-based Optimization.

Cited By

• http://scholar.google.com/scholar?q=%222015%22+Adam%3A+A+Method+for+Stochastic+Optimization

Quotes

Abstract

We introduce Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments. The method is straightforward to implement, is computationally efficient, has little memory requirements, is invariant to diagonal rescaling of the gradients, and is well suited for problems that are large in terms of data and/or parameters. The method is also appropriate for non-stationary objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive interpretations and typically require little tuning. Some connections to related algorithms, on which Adam was inspired, are discussed. We also analyze the theoretical convergence properties of the algorithm and provide a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework. Empirical results demonstrate that Adam works well in practice and compares favorably to other stochastic optimization methods. Finally, we discuss AdaMax, a variant of Adam based on the infinity norm.

BibTeX

@inproceedings{2015_AdamAMethodforStochasticOptimiz,
  author    = {Diederik P. Kingma and
               [[Jimmy Ba]]},
  editor    = {Yoshua Bengio and
               Yann LeCun},
  title     = {Adam: A Method for Stochastic Optimization},
  booktitle = {Proceedings of the 3rd International Conference on Learning Representations (ICLR 2015),
               San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings},
  year      = {2015},
  url       = {http://arxiv.org/abs/1412.6980},
}

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 AdamAMethodforStochasticOptimiz	Diederik P. Kingma Jimmy Ba			Adam: A Method for Stochastic Optimization						2015