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Blockwise Stabilized Adaptive Cubic Regularization with Subsolvers via Recurrence
Overparameterized networks often have ill-conditioned, saddle rich loss landscapes. They are usually trained with first-order methods that struggle on those landscapes, while many second-order methods stay infeasible at scale. Some scalable cubic methods replace the Hessian by a computationally chea
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