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Testing Distributions of Huge Objects

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abstract

We initiate a study of a new model of property testing that is a hybrid of testing properties of distributions and testing properties of strings. Specifically, the new model refers to testing properties of distributions, but these are distributions over huge objects (i.e., very long strings). Accordingly, the model accounts for the total number of local probes into these objects (resp., queries to the strings) as well as for the distance between objects (resp., strings), and the distance between distributions is defined as the earth mover's distance with respect to the relative Hamming distance between strings. We study the query complexity of testing in this new model, focusing on three directions. First, we try to relate the query complexity of testing properties in the new model to the sample complexity of testing these properties in the standard distribution testing model. Second, we consider the complexity of testing properties that arise naturally in the new model (e.g., distributions that capture random variations of fixed strings). Third, we consider the complexity of testing properties that were extensively studied in the standard distribution testing model: Two such cases are uniform distributions and pairs of identical distributions.

fields

cs.DS 1

years

2024 1

verdicts

CONDITIONAL 1

representative citing papers

Online versus Offline Adversaries in Property Testing

cs.DS · 2024-11-27 · conditional · novelty 8.0

Online (adaptive) adversarial manipulation of inputs is incomparable to offline (pre-committed) manipulation in query complexity, and can require exponentially more random bits.

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  • Online versus Offline Adversaries in Property Testing cs.DS · 2024-11-27 · conditional · none · ref 18 · internal anchor

    Online (adaptive) adversarial manipulation of inputs is incomparable to offline (pre-committed) manipulation in query complexity, and can require exponentially more random bits.