A bundle Newton method for nonsmooth optimization achieves local quadratic convergence given the cardinality of the optimal active set.
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A smoothing stochastic gradient descent algorithm is introduced for non-smooth stochastic compositional optimization, achieving 1/T^{1/4} rate for convex cases and similar guarantees under other convexity settings.
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A simple Newton method for local nonsmooth optimization
A bundle Newton method for nonsmooth optimization achieves local quadratic convergence given the cardinality of the optimal active set.
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Non-smooth stochastic gradient descent using smoothing functions
A smoothing stochastic gradient descent algorithm is introduced for non-smooth stochastic compositional optimization, achieving 1/T^{1/4} rate for convex cases and similar guarantees under other convexity settings.