Online contextual influence maximization with costly observations

• Main Authors: SARITAC, Omer, KARAKURT, Altug, TEKIN, Cem
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Influence maximization; combinatorial bandits; social networks; approximation algorithms; costly observations; regret bounds; Operations and Supply Chain Management; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/7602
• Institution: Singapore Management University

In the online contextual influence maximization problem with costly observations, the learner faces a series of epochs in each of which a different influence spread process takes place over a network. At the beginning of each epoch, the learner exogenously influences (activates) a set of seed nodes...