Attribute-Efficient Learning

Jyrki Kivinen

Abstract:

1987; Littlestone
Given here is a basic formulation using the online mistake-bound model, which was used by Littlestone [9] in his seminal work.

Fix a class C of Boolean functions over n variables. To start a learning scenario, a target function f∗ ∈ C is chosen but not revealed to the learning algorithm. Learning then proceeds in a sequence of trials. At trial t, an input \(\boldsymbol{x}_{t} \in \{ 0,1\}^{n}\)