Foivos Alimisis
Published 2024-02-19Version 1
In this work, we state a general conjecture on the solvability of optimization problems via algorithms with linear convergence guarantees. We make a first step towards examining its correctness by fully characterizing the problems that are solvable via Riemannian gradient descent with linear convergence.
Performance Bounds for the $k$-Batch Greedy Strategy in Optimization Problems with Curvatures
Duality of optimization problems with gauge functions
Two optimization problems in thermal insulation
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