Published as a conference paper at NeurIPS 2026
High-arity Sample Compression
Leonardo Coregliano, William Opich
Abstract
Recently, a series of works have started studying variations of concepts from learning theory for product spaces, which can be collected under the name high-arity learning theory. In this work, we consider a high-arity variant of sample compression schemes and we prove that the existence of a high-arity sample compression scheme of non-trivial quality implies high-arity PAC learnability.
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