Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds
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DOI: 10.1109/tit.2022.3146206
Abstract: We propose novel randomized optimization methods for high-dimensional convex problems based on restrictions of variables to random subspaces. We consider oblivious and data-adaptive subspaces and study their approximation properties via convex duality and Fenchel conjugates.… read more here.
Keywords: optimization; adaptive oblivious; high dimensional; subspace ... See more keywords