We consider the problem of detecting a small subset of defective items from a large set via
non-adaptive" random pooling" group tests. We consider both the case when the …

We consider the probabilistic group testing problem where d random defective items in a
large population of N items are identified with high probability by applying binary tests. It is …

An important problem in the context of supervised machine learning is designing systems
which are interpretable by humans. In domains such as law, medicine, and finance that deal …

In this paper, we introduce a variation of the group testing problem capturing the idea that a
positive test requires a combination of multiple “types” of items. Specifically, we assume that …

We propose a novel group testing method, termed semiquantitative group testing (SQGT),
motivated by a class of problems arising in genome screening experiments. The SQGT is a …

A binary code is said to be a disjunctive (s, ℓ) cover-free code if it is an incidence matrix of a
family of sets where the intersection of any ℓ sets is not covered by the union of any other s …

We consider non-adaptive threshold group testing for identification of up to d defective items
in a set of n items, where a test is positive if it contains at least 2≤ u≤ d defective items, and …

The basic goal in combinatorial group testing is to identify a set of up to d defective items
within a large population of size n≫ d using a pooling strategy. Namely, the items can be …

We consider threshold group testing–a generalization of a well known and thoroughly
examined problem of combinatorial group testing. In the classical setting, the goal is to …

We will discuss superimposed codes and non-adaptive group testing designs arising from
the potentialities of compressed genotyping models in molecular biology. The given paper …