Algorithms & Randomness Center (ARC)
Amin Coja-Oghlan (Goethe University, Frankfurt)
Monday, April 12, 2021
Virtual via Bluejeans - 11:00 am
Title: Group Testing
Abstract: In the group testing problem the goal is to identify a small number of infected individuals within a large population by conducting as small a number of tests as possible. The tests are assumed to accept pools of individuals rather than just single individuals, with a test returning a positive result iff at least one individual in the pool is actually infected. Mathematically we ask for information-theoretic lower bounds showing that a certain number of tests is necessary to correctly learn the set of infected individuals as well as algorithmic upper bounds showing that a certain number of tests suffice. In this talk I am going to present some mathematical results, some experimental results and some open problems.
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