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Found 2 papers, 1 papers with code
Newton-ADMM: A Distributed GPU-Accelerated Optimizer for Multiclass Classification Problems
First-order optimization methods, such as stochastic gradient descent (SGD) and its variants, are widely used in machine learning applications due to their simplicity and low per-iteration costs.
GPU Accelerated Sub-Sampled Newton's Method
In particular, in convex settings, we consider variants of classical Newton\textsf{'}s method in which the Hessian and/or the gradient are randomly sub-sampled.
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