Optimal budget allocation: Theoretical guarantee and efficient algorithm

Tasuku Soma, Naonori Kakimura, Kazuhiro Inaba, Ken Ichi Kawarabayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Citations (Scopus)

Abstract

2014 We consider the budget allocation problem over bipartite influence model proposed by Alon et al. (Alon et al., 2012). This problem can be viewed as the well-known influence maximization problem with budget constraints. We first show that this problem and its much more general form fall into a general setting; namely the monotone submodular function maximization over integer lattice subject to a knapsack constraint. Our framework includes Alon et al.'s model, even with a competitor and with cost. We then give a (1 - 1/e)-approximation algorithm for this more general problem. Furthermore, when influence probabilities are nonincreasing, we obtain a faster (1 - 1/e)-approximation algorithm, which runs essentially in linear time in the number of nodes. This allows us to implement our algorithm up to almost 10M edges (indeed, our experiments tell us that we can implement our algorithm up to 1 billion edges. It would approximately take us only 500 seconds.).

Original languageEnglish
Title of host publication31st International Conference on Machine Learning, ICML 2014
PublisherInternational Machine Learning Society (IMLS)
Pages556-568
Number of pages13
Volume1
ISBN (Electronic)9781634393973
Publication statusPublished - 2014
Externally publishedYes
Event31st International Conference on Machine Learning, ICML 2014 - Beijing, China
Duration: 2014 Jun 212014 Jun 26

Other

Other31st International Conference on Machine Learning, ICML 2014
CountryChina
CityBeijing
Period14/6/2114/6/26

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Approximation algorithms
Costs
Experiments

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

Cite this

Soma, T., Kakimura, N., Inaba, K., & Kawarabayashi, K. I. (2014). Optimal budget allocation: Theoretical guarantee and efficient algorithm. In 31st International Conference on Machine Learning, ICML 2014 (Vol. 1, pp. 556-568). International Machine Learning Society (IMLS).

Optimal budget allocation : Theoretical guarantee and efficient algorithm. / Soma, Tasuku; Kakimura, Naonori; Inaba, Kazuhiro; Kawarabayashi, Ken Ichi.

31st International Conference on Machine Learning, ICML 2014. Vol. 1 International Machine Learning Society (IMLS), 2014. p. 556-568.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Soma, T, Kakimura, N, Inaba, K & Kawarabayashi, KI 2014, Optimal budget allocation: Theoretical guarantee and efficient algorithm. in 31st International Conference on Machine Learning, ICML 2014. vol. 1, International Machine Learning Society (IMLS), pp. 556-568, 31st International Conference on Machine Learning, ICML 2014, Beijing, China, 14/6/21.
Soma T, Kakimura N, Inaba K, Kawarabayashi KI. Optimal budget allocation: Theoretical guarantee and efficient algorithm. In 31st International Conference on Machine Learning, ICML 2014. Vol. 1. International Machine Learning Society (IMLS). 2014. p. 556-568
Soma, Tasuku ; Kakimura, Naonori ; Inaba, Kazuhiro ; Kawarabayashi, Ken Ichi. / Optimal budget allocation : Theoretical guarantee and efficient algorithm. 31st International Conference on Machine Learning, ICML 2014. Vol. 1 International Machine Learning Society (IMLS), 2014. pp. 556-568
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