Non-adaptive group testing: Explicit bounds and novel algorithms
Non-adaptive group testing: Explicit bounds and novel algorithms
We present computationally efficient and provably correct algorithms with near-optimal sample-complexity for noisy non-adaptive group testing. Group testing involves grouping arbitrary subsets of items into pools. Each pool is then tested to identify the defective items, which are usually assumed to be sparsely distributed. We consider random non-adaptive pooling where …