Real-time Television ROI Tracking using Mirrored Experimental Designs

Abstract. Real-time conversion tracking is the holy grail of TV advertisers. We show how to use thousands of tiny areas available via commercial cable and satellite systems to create low cost tracking cells. These areas are created as "mirrors" of a national campaign, and run in parallel with it. With properly controlled areas, it is possible to calculate national effects due to TV using statistical methods. We show performance of the method on a large-scale TV advertising campaign where it was used successfully to maintain a real-time CPA target of $60 for 179 days 1

Bid Shading in The Brave New World of First-Price Auctions

Online auctions play a central role in online advertising, and are one of the main reasons for the industry's scalability and growth. With great changes in how auctions are being organized, such as changing the second- to first-price auction type, advertisers and demand platforms are compelled to adapt to a new volatile environment. Bid shading is a known technique for preventing overpaying in auction systems that can help maintain the strategy equilibrium in first-price auctions, tackling one of its greatest drawbacks. In this study, we propose a machine learning approach of modeling optimal bid shading for non-censored online first-price ad auctions. We clearly motivate the approach and extensively evaluate it in both offline and online settings on a major demand side platform. The results demonstrate the superiority and robustness of the new approach as compared to the existing approaches across a range of performance metrics.Comment: In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), October 19-23, 2020, Virtual Event, Irelan

Relative position (susceptible to countermeasure)

Abstract W

A Statistical Link between Learning and Evolution

Widely replicated experimental findings show that faced with multiple variable reward outcomes, animals sample each proportional to their mean payoff. This finding is explained computationally using the Holland theorem, in which this style of sampling is optimal given certain assumptions about the distribution. Other adaptive phenomena which seem to be consistent with this law are discussed, and it is suggested that the 'adaptive problem' may be broadly similar across different domains. 1 Response Matching: A curious behavioural constant The matching law was first uncovered by Richard Herrnstein in operant conditioning experiments in the 1950s. Herrnstein was examining how pigeons behave on a concurrent reinforcement schedule pecking at two response keys, k 1 and k 2 . Reinforcement was supplied at a different rate for each key, given by r 1 (k 1 ) and r 2 (k 2 ). Herrnstein found that the relative frequency of responding, b 1 to k 1 and b 2 to k 2 was equal to the relation: b 1 b..

Representation Operators and Computation

This paper derives results about the impact of representation and search operators on the Computational Complexity of a problem. A model of computation is introduced based on a directed graph structure, and representation and search are defined to be respectively the vertices and edges of this graph. Changing either the representation or the search algorithm leads to different possible graphs, and hence have different complexity classes. The final section explores the role of representation in reducing time complexity in Artificial Intelligence. Keywords: representation, redescription, recoding June 6, 1998 Page: 2 1.0 Introduction In solving real-world problems, a significant part of the task is finding a good encoding scheme. Another is finding an algorithm which manipulates the data efficiently. While the second enterprise (algorithm design) has been analysed in Computer Science, the first, selection of a representation, has been ignored or grouped with algorithm design. This pap..

Regulation of Complex Systems

This paper suggests a method for optimizing complex systems using a combination of cheap local and more expensive global dynamics. Two extrema for Optimization strategie