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The oracle Complexity of Smooth Convex Optimization in Nonstandard Settings
Published on Aug 20, 20151580 Views
First-order convex minimization algorithms are currently the methods of choice for large-scale sparse – and more generally parsimonious – regression models. We pose the question on the limits of per
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Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings00:00
Oracle-based Algorithms - 100:20
Oracle-based Algorithms - 201:26
Oracle-based Algorithms - 302:01
Non-standard Settings - 102:31
ℓp/ℓq-Lower Bounds03:00
Non-standard Settings - 204:33