Bandit Convex Optimisation
arxiv(2024)
摘要
Bandit convex optimisation is a fundamental framework for studying
zeroth-order convex optimisation. These notes cover the many tools used for
this problem, including cutting plane methods, interior point methods,
continuous exponential weights, gradient descent and online Newton step. The
nuances between the many assumptions and setups are explained. Although there
is not much truly new here, some existing tools are applied in novel ways to
obtain new algorithms. A few bounds are improved in minor ways.
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