89 citations · 211 across the 10 of their papers we have counts for
10 papers
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions
Wei Zhang, Yanjun Han, Zhengyuan Zhou +2
With the advent and increasing consolidation of e-commerce, digital advertising has very recently replaced traditional advertising as the main marketing force in the economy. In th…
Mid-flight Forecasting for CPA Lines in Online Advertising
Hao He, Tian Zhou, Lihua Ren +2
For Verizon MediaDemand Side Platform(DSP), forecasting of ad campaign performance not only feeds key information to the optimization server to allow the system to operate on a hig…
An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions
Tian Zhou, Hao He, Shengjun Pan +9
Since 2019, most ad exchanges and sell-side platforms (SSPs), in the online advertising industry, shifted from second to first price auctions. Due to the fundamental difference bet…
: Field-matrixed Factorization Machines for Recommender Systems
Yang Sun, Junwei Pan, Alex Zhang +1
Click-through rate (CTR) prediction plays a critical role in recommender systems and online advertising. The data used in these applications are multi-field categorical data, where…
Bid Shading by Win-Rate Estimation and Surplus Maximization
Shengjun Pan, Brendan Kitts, Tian Zhou +8
This paper describes a new win-rate based bid shading algorithm (WR) that does not rely on the minimum-bid-to-win feedback from a Sell-Side Platform (SSP). The method uses a modifi…
Bid Shading in The Brave New World of First-Price Auctions
Djordje Gligorijevic, Tian Zhou, Bharatbhushan Shetty +4
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 o…
Learning to Bid Optimally and Efficiently in Adversarial First-price Auctions
Yanjun Han, Zhengyuan Zhou, Aaron Flores +2
First-price auctions have very recently swept the online advertising industry, replacing second-price auctions as the predominant auction mechanism on many platforms. This shift ha…
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving
Wei Deng, Junwei Pan, Tian Zhou +3
Click-through rate (CTR) prediction is a crucial task in online display advertising. The embedding-based neural networks have been proposed to learn both explicit feature interacti…
Time-Aware Prospective Modeling of Users for Online Display Advertising
Djordje Gligorijevic, Jelena Gligorijevic, Aaron Flores
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 p…
Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising
Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz +2
Conversion prediction plays an important role in online advertising since Cost-Per-Action (CPA) has become one of the primary campaign performance objectives in the industry. Unlik…