Tutorials and Technical Briefings at ISEC 2025
Atul Kumar
ISEC 2025
Consider a set of n advertisements (hereafter called "ads") A = {A1, . . . , An} competing to be placed in a planning horizon which is divided into N time intervals called slots. An ad Ai is specified by its size si and frequency wi. The size si represents the amount of space the ad occupies, in a slot. Ad Ai is said to be scheduled if exactly wi copies of A i are placed in the slots subject to the restriction that a slot contains at most one copy of an ad. In this paper, we consider two problems. The MINSPACE problem minimizes the maximum fullness among all slots in a feasible schedule where the fullness of a slot is the sum of the sizes of ads assigned to the slot. For the MAXSPACE problem, in addition, we are given a common maximum fullness S for all slots. The total size of the ads placed in a slot cannot exceed S. The objective is to find a feasible schedule A′ ⊆ A of ads such that the total occupied slot space ΣAi∈A′w isi maximized. We examine the complexity status of both problems and provide heuristics with performance guarantees.
Atul Kumar
ISEC 2025
Ira Pohl
Artificial Intelligence
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025