A Model-Agnostic Randomized Learning Framework based on Random Hypothesis Subspace Sampling

Yiting Cao, Chao Lan

Abstract: We propose a model-agnostic randomized learning framework based on Random Hypothesis Subspace Sampling (RHSS). Given any hypothesis class, it randomly samples $k$ hypotheses and learns a near-optim...