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Found 5 papers, 1 papers with code
Advertising Media and Target Audience Optimization via High-dimensional Bandits
We present a data-driven algorithm that advertisers can use to automate their digital ad-campaigns at online publishers.
Comparison Lift: Bandit-based Experimentation System for Online Advertising
Second, by adapting experimental design to information acquired during the test, it reduces substantially the cost of experimentation to the advertiser.
Online Causal Inference for Advertising in Real-Time Bidding Auctions
Leveraging the economic structure of first- and second-price auctions, we first show that the effects of advertising are identified by the optimal bids.
Online Evaluation of Audiences for Targeted Advertising via Bandit Experiments
The product is currently deployed on the advertising platform of JD. com, an eCommerce company and a publisher of digital ads in China.
Parallel Experimentation and Competitive Interference on Online Advertising Platforms
This paper studies the measurement of advertising effects on online platforms when parallel experimentation occurs, that is, when multiple advertisers experiment concurrently.
