Near-Optimal Sparsity-Constrained Group Testing: Improved Bounds and Algorithms
Near-Optimal Sparsity-Constrained Group Testing: Improved Bounds and Algorithms
Recent advances in noiseless non-adaptive group testing have led to a precise asymptotic characterization of the number of tests required for high-probability recovery in the sublinear regime <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k = n^{\theta }$ </tex-math></inline-formula> (with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\theta \in (0,1)$ </tex-math></inline-formula> ), with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> …