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It is proved that the proposed step size preserves the descent property of the MCondG method, and has an improved worst-case complexity bound compared with the original adaptive step size strategy.
This work proposes a fully Hessian-inverse-free stochastic gradient method for SMOBO which is computationally efficient due to the use of a decoupling approach, and employs a momentum-like gradient estimate to replace the stochastic gradients with their moving average, thereby mitigating the errors induced by dynamic w...
A preconditioned proximal Barzilai--Borwein method for multiobjective composite optimization that combines objective-wise Barzilai--Borwein scaling with a common preconditioner that captures shared curvature information is proposed.
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