Introduces bAdag, an AdaGrad-based block coordinate gradient method with ergodic sublinear convergence proofs for smooth nonconvex objectives under block Lipschitz gradient assumptions, covering cyclic, uniform random, and Gauss-Southwell selection plus box constraints.
Compl exity of adagrad and other first-order methods for nonconvex optimization problems with bounds constraints
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bAdag: an adaptive block coordinate gradient method for smooth nonconvex functions
Introduces bAdag, an AdaGrad-based block coordinate gradient method with ergodic sublinear convergence proofs for smooth nonconvex objectives under block Lipschitz gradient assumptions, covering cyclic, uniform random, and Gauss-Southwell selection plus box constraints.