Learners that Use Little Information

14 Oct 2017Raef BassilyShay MoranIdo NachumJonathan ShaferAmir Yehudayoff

We study learning algorithms that are restricted to using a small amount of information from their input sample. We introduce a category of learning algorithms we term $d$-bit information learners, which are algorithms whose output conveys at most $d$ bits of information of their input... (read more)

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