Positive linear programming (PLP), also known as packing and covering linear programs, is an important class of problems frequently found in fields such as network science, operations research, or economics. In this work we demonstrate that all PLP problems can be represented using a network structure, revealing new key insights that lead to new polynomial-time algorithms.
30 Jun 2020
Large data sets can contain patterns at multiple scales (spatial, temporal, etc.). In practice, it is useful for data exploration…