We consider the search problems in which the goal is definite and the search methods are given. The most general search problem is to find unknown items in a given finite set by asking questions relating to the contents of subsets. We generally look for search strategies which are more economical in the number of queries and less time consuming in determining the unknown items from queries outcomes. Besides dealing with search problems from real applications, we further set up and study search problems that have high potential of being applied.
Group testing is probably the most well-known search problem; besides, graph learning problem, a search problem motivated by applications in genome sequencing, have also been studied with much attention. In this talk, I will introduce my recent work on combinatorial group testing on inhibitor complex model, threshold group testing problems and graph learning problems.
Group testing is probably the most well-known search problem; besides, graph learning problem, a search problem motivated by applications in genome sequencing, have also been studied with much attention. In this talk, I will introduce my recent work on combinatorial group testing on inhibitor complex model, threshold group testing problems and graph learning problems.