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We consider the problem of finding critical points of functions that are non-convex and non-smooth.
On functions representable as a difference of convex functions
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Variational analysis
R. T. Rockafellar and R. J.-B. Wets · 2009
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Proximal alternating minimization and projection methods for nonconvex problems: An approach based on the Kurdyka-Lojasiewicz inequality
H. Attouch, J. Bolte, P. Redont, and A. Soubeyran · 2010
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C. Cartis, N. I. Gould, and P. L. Toint · 2010
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A. A. Ahmadi, A. Olshevsky, P. A. Parrilo, and J. N. Tsitsiklis · 2013
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A complete characterization of the gap between convexity and sos-convexity
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Gradient descent only converges to minimizers
J. D. Lee, M. Simchowitz, M. I. Jordan, and B. Recht · 2016
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G. Li and T. K. Pong · 2016
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Convergence analysis of a proximal point algorithm for minimizing differences of functions
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Lower bounds for finding stationary points i
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No spurious local minima in nonconvex low rank problems: A unified geometric analysis
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DC formulations and algorithms for sparse optimization problems
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Convergence analysis of two-layer neural networks with relu activation
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A globally convergent algorithm for nonconvex optimization based on block coordinate update
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