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Found 8 papers, 0 papers with code
An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions
Since 2019, most ad exchanges and sell-side platforms (SSPs), in the online advertising industry, shifted from second to first price auctions.
Bid Shading by Win-Rate Estimation and Surplus Maximization
We found that bid shading, in general, can deliver significant value to advertisers, reducing price per impression to about 55% of the unshaded cost.
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.
Time-Aware Prospective Modeling of Users for Online Display Advertising
Prospective display advertising poses a great challenge for large advertising platforms as the strongest predictive signals of users are not eligible to be used in the conversion prediction systems.
Deep Attention Model for Triage of Emergency Department Patients
Optimization of patient throughput and wait time in emergency departments (ED) is an important task for hospital systems.
Modeling Customer Engagement from Partial Observations
It is of high interest for a company to identify customers expected to bring the largest profit in the upcoming period.
Improving confidence while predicting trends in temporal disease networks
Our experiments demonstrate benefits of using graph information in modeling temporal disease properties as well as improvements in uncertainty estimation provided by given extensions of the Gaussian Conditional Random Fields method.
Semi-supervised learning for structured regression on partially observed attributed graphs
We also show that the method can be useful for optimizing the costs of data collection in climate applications via active reduction of the number of weather stations to consider.
