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20242026
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cs.DS2026

Distribution-Free Halfspace Testing with Samples

Xi Chen, Renato Ferreira Pinto, Nathaniel Harms +2

We prove a tight lower bound on the number of samples required for testing halfspaces over , in the distribution-free sample-based model where the underlying…

cs.DS2026

Model-agnostic super-resolution in high dimensions

Xi Chen, Anindya De, Yizhi Huang +3

The problem of super-resolution, roughly speaking, is to reconstruct an unknown signal to high accuracy, given (potentially noisy) information about its low-degree Fourier coeffici…

cs.DS2026

Sublinear-query relative-error testing of halfspaces

Xi Chen, Anindya De, Yizhi Huang +3

The relative-error property testing model was introduced in [CDHLNSY24] to facilitate the study of property testing for "sparse" Boolean-valued functions, i.e. ones for which only…

cs.DS2025

Testing noisy low-degree polynomials for sparsity

Yiqiao Bao, Anindya De, Shivam Nadimpalli +2

We consider the problem of testing whether an unknown low-degree polynomial over is sparse versus far from sparse, given access to noisy evaluations of the polyn…

cs.DS2025

Faster exact learning of k-term DNFs with membership and equivalence queries

Josh Alman, Shivam Nadimpalli, Shyamal Patel +1

In 1992 Blum and Rudich [BR92] gave an algorithm that uses membership and equivalence queries to learn -term DNF formulas over in time , improv…

cs.DS2025

DNF Learning via Locally Mixing Random Walks

Josh Alman, Shivam Nadimpalli, Shyamal Patel +1

We give two results on PAC learning DNF formulas using membership queries in the challenging "distribution-free" learning framework, where learning algorithms must succeed for an a…