Bandit Convex Optimisation
It provides a comprehensive overview for researchers in optimization, but is largely incremental in its contributions.
The book addresses bandit convex optimization, a framework for zeroth-order convex optimization, by applying existing tools in novel ways to develop new algorithms and achieve minor improvements in some bounds.
Bandit convex optimisation is a fundamental framework for studying zeroth-order convex optimisation. This book covers 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.