• Sample-Augmented Online Steiner Forest
  • Project Year: 2026
  • REU Student (s):   Gal Ben-Ami | Bar-Ilan University   |   Ryan Liu | Brown University  
  • Project Mentor (s) : Roie Levin - Computer Science
  • Project Abstract:

    The online Steiner forest problem asks an algorithm to connect demand pairs arriving sequentially in a weighted undirected graph, without knowledge of future demands and without deleting previously purchased edges. Whereas the offline problem has constant-factor approximations, the optimal ratio in the fully online setting is O(log k) for k demands. We study Steiner forest in the online algorithms with a sample framework, which interpolates between these settings by revealing each demand independently with probability p before the online phase. Previous work by Argue et al. 2022 gives an O(log 1/p) ratio for Steiner tree. We developed an O(1/p)-competitive algorithm for Steiner forest, giving a guarantee independent of the total number of demands.