Robust Adaptive Submodular Maximization

References

• Asadpour A, Nazerzadeh H (2016) Maximizing stochastic monotone submodular functions. Management Sci. 62:2374–2391.Link, Google Scholar
• Asadpour A, Nazerzadeh H, Saberi A (2008) Stochastic submodular maximization. Proc. Internat. Workshop on Internet and Network Econom. (Springer, Berlin), 477–489.Google Scholar
• Badanidiyuru A, Vondrák J (2014) Fast algorithms for maximizing submodular functions. Proc. 25th Annual ACM-SIAM Sympos. on Discrete Algorithms (SIAM, Philadelphia), 1497–1514.Google Scholar
• Badanidiyuru A, Mirzasoleiman B, Karbasi A, Krause A (2014) Streaming submodular maximization: Massive data summarization on the fly. Proc. 20th ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining (ACM, New York), 671–680.Google Scholar
• Calinescu G, Chekuri C, Pál M, Vondrák J (2007) Maximizing a submodular set function subject to a matroid constraint. Proc. Internat. Conf. on Integer Programming and Combinatorial Optim. (Springer, Berlin), 182–196.Google Scholar
• Cuong NV, Lee WS, Ye N (2014) Near-optimal adaptive pool-based active learning with general loss. Uncertainty Artificial Intelligence: Proc. 30th Conf. (AUAI Press), 122–131.Google Scholar
• Ene A, Nguyen HL (2018) Toward nearly-linear time algorithms for submodular maximization with a matroid constraint. Preprint, submitted November 19, https://arxiv.org/abs/1811.07464.Google Scholar
• Feige U (1998) A threshold of ln n for approximating set cover. J. ACM 45:634–652.Crossref, Google Scholar
• Golovin D, Krause A (2011a) Adaptive submodular optimization under matroid constraints. Preprint, submitted January 24, https://arxiv.org/abs/1101.4450.Google Scholar
• Golovin D, Krause A (2011b) Adaptive submodularity: Theory and applications in active learning and stochastic optimization. J. Artificial Intelligence Res. 42:427–486.Google Scholar
• Guillory A, Bilmes J (2010) Interactive submodular set cover. Proc. 27th Internat. Conf. on Machine Learn. (IEEE, Piscataway, NJ), 415–422.Google Scholar
• Kempe D, Mahdian M (2008) A cascade model for externalities in sponsored search. Proc. Internat. Workshop on Internet and Network Econom. (Springer, Berlin), 585–596.Google Scholar
• Krause A, Guestrin C (2007) Near-Optimal Observation Selection Using Submodular Functions, vol. 7 (AAAI, Palo Alto, CA), 1650–1654.Google Scholar
• Leskovec J, Krause A, Guestrin C, Faloutsos C, VanBriesen J, Glance N (2007) Cost-effective outbreak detection in networks. Proc. 13th ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining (ACM, New York), 420–429.Google Scholar
• Mirzasoleiman B, Badanidiyuru A, Karbasi A (2016) Fast constrained submodular maximization: Personalized data summarization. Internat. Conf. Machine Learn. (PMLR, New York), 1358–1367.Google Scholar
• Mirzasoleiman B, Badanidiyuru A, Karbasi A, Vondrák J, Krause A (2015) Lazier than lazy greedy. Proc. 29th AAAI Conf. on Artificial Intelligence (AAAI, Palo Alto, CA).Google Scholar
• Tang S (2021a) Beyond pointwise submodularity: Non-monotone adaptive submodular maximization in linear time. Theoretical Comput. Sci. 850:249–261.Crossref, Google Scholar
• Tang S (2021b) Beyond pointwise submodularity: Non-monotone adaptive submodular maximization subject to knapsack and k-system constraints. Proc. Internat. Conf. on Modelling, Comput. and Optim. in Inform. Systems and Management Sci. (Springer, Berlin), 16–27.Google Scholar
• Tang S, Yuan J (2020) Influence maximization with partial feedback. Oper. Res. Lett. 48:24–28.Crossref, Google Scholar
• Tang S, Yuan J (2021a) Adaptive regularized submodular maximization. Proc. 32nd Internat. Sympos. on Algorithms and Comput. (Schloss Dagstuhl-Leibniz-Zentrum für Informatik).Google Scholar
• Tang S, Yuan J (2021b) Non-monotone adaptive submodular meta-learning. Proc. SIAM Conf. on Appl. and Comput. Discrete Algorithms (SIAM, Philadelphia), 57–65.Google Scholar
• Tang S, Yuan J (2022a) Group fairness in adaptive submodular maximization. Preprint, submitted July 7, https://arxiv.org/abs/2207.03364.Google Scholar
• Tang S, Yuan J (2022b) Optimal sampling gaps for adaptive submodular maximization. Proc. Conf. AAAI Artificial Intelligence, vol. 36 (AAAI, Palo Alto, CA), 8450–8457.Crossref, Google Scholar
• Tang S, Yuan J (2022c) Partial-monotone adaptive submodular maximization. Preprint, submitted July 26, https://arxiv.org/abs/2207.12840.Google Scholar
• Yuan J, Tang S (2017) No time to observe: adaptive influence maximization with partial feedback. Proc. 26th Internat. Joint Conf. on Artificial Intelligence 3908–3914.Google Scholar