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Managing advertising campaigns - an approximate planning approach.

, , , and . Frontiers Comput. Sci., 6 (2): 209-229 (2012)

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Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management., , and . CAP, page 183-184. PUG, (2005)Distributionally Robust Reinforcement Learning., , and . CoRR, (2019)Managing advertising campaigns - an approximate planning approach., , , and . Frontiers Comput. Sci., 6 (2): 209-229 (2012)Cold-start Problems in Recommendation Systems via Contextual-bandit Algorithms., , and . CoRR, (2014)EdiBERT: a generative model for image editing., , , and . Trans. Mach. Learn. Res., (2023)Lessons from the AdKDD'21 Privacy-Preserving ML Challenge., , , , , , , , and . WWW, page 2026-2035. ACM, (2022)Advertising Campaigns Management: Should We Be Greedy?, , , and . ICDM, page 821-826. IEEE Computer Society, (2010)Recurrent Neural Networks for Long and Short-Term Sequential Recommendation., , , and . CoRR, (2018)ICML Exploration & Exploitation Challenge: Keep it simple!, , and . ICML On-line Trading of Exploration and Exploitation, volume 26 of JMLR Proceedings, page 62-85. JMLR.org, (2012)Fairness-Aware Learning for Continuous Attributes and Treatments., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4382-4391. PMLR, (2019)