Abstract
In Learning Reductions, you reduce to a simpler machine learning problem, apply a solver for that problem, and then use the solution on the simpler problem to solve a more complex problem. Learning reductions have been used to create exponentially more efficient solutions to Multiclass classification, Contextual Bandit learning and exploration, and Active Learning. I will discuss several families of learning reductions, their applications, and limits.