2 problems

Almost-sure global convergence of the subgradient method for \ell_1-norm rank-one symmetric matrix factorization
Consider the $\ell_1$ -norm rank-one symmetric matrix factorization problem and initialize the subgradient method randomly, with an initialization distribution absolutely continuous…
openFrom papersmatrix-factorization nonsmooth-optimization subgradient-methods
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4
Tight subgradient-norm convergence conjecture for the proximal point algorithm
Subgradient-norm convergence conjecture. For every iterate $x_N$ , there exists a subgradient $g_N\in\partial f(x_N)$ such that
openFrom papersconvex-optimization proximal-point-algorithm subgradient-methods
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3

Almost-sure global convergence of the subgradient method for \ell_1-norm rank-one symmetric matrix factorization