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Asymptotic Lower Bounds for Continuous Optimization
Nonasymptotic convergence rates for optimization problems have been extensively studied across a wide range of settings, with carefully constructed worst-case instances establishing matching lower bounds for many algorithm classes. Recent work has shown, however, that these rates can often be improv
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