研究论文
Online Causal Inference for Advertising in Real-Time Bidding Auctions
Caio Waisman, Harikesh S. Nair, Carlos Carrión
Northwestern University Google (United States) Georgia Institute of Technology
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摘要与影响
摘要 · 完整
This paper introduces a multiarmed bandit approach to estimate advertising effectiveness and manage experimentation costs in real-time bidding auctions concurrently.
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学术脉络
学科主题
计算机 / AIAuction Theory and Applications
Advanced Bandit Algorithms Research · Consumer Market Behavior and Pricing
参考文献 116
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Thompson Sampling for Complex Online Problems
被引 122Aditya Gopalan, Shie Mannor, Yishay Mansour · 2014
Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences.
被引 604Felix D. Schönbrodt, Eric‐Jan Wagenmakers, Michael Zehetleitner · Psychological Methods · 2015
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Comparison Lift: Bandit-based Experimentation System for Online Advertising
被引 11Tong Geng, Xiliang Lin, Harikesh S. Nair · Proceedings of the AAAI Conference on Artificial Intelligence · 2021
Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?
被引 7Fabrizio Ruggeri, David Banks, William S. Cleveland · Applied Stochastic Models in Business and Industry · 2025
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