Painless Stochastic Conjugate Gradient for Large-Scale Machine Learning

Conjugate gradient (CG), as an effective technique to speed up gradient descent algorithms, has shown great potential and has widely been used for large-scale machine-learning problems. However, CG and its variants have not been devised for the stochastic setting, which makes them extremely unstable...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 35; číslo 10; s. 14645 - 14658
Hlavný autor:	Yang, Zhuang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.10.2024
Predmet:	Adaptive step size Convergence Heuristic algorithms Linear programming Machine learning Machine learning algorithms mini-batches Noise measurement Optimization stochastic conjugate gradient (SCG) variance reduction
ISSN:	2162-237X, 2162-2388, 2162-2388
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