29 citations · 67 across the 8 of their papers we have counts for
13 papers
Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch
Paul Brunzema, Louis Tiao, Nhat Le +3
Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by generic statistical priors.…
Location Aware Embedding for Geotargeting in Sponsored Search Advertising
Jelena Gligorijevic, Djordje Gligorijevic, Aravindan Raghuveer +2
Web search has become an inevitable part of everyday life. Improving and monetizing web search has been a focus of major Internet players. Understanding the context of web search q…
Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems
Jiang Liu, John Martabano Landy, Yao Xuan +14
Modern computational advertising platforms typically rely on recommendation systems to predict user responses, such as click-through rates, conversion rates, and other optimization…
Learning Concave Bid Shading Strategies in Online Auctions via Measure-valued Proximal Optimization
Iman Nodozi, Djordje Gligorijevic, Abhishek Halder
This work proposes a bid shading strategy for first-price auctions as a measure-valued optimization problem. We consider a standard parametric form for bid shading and formulate th…
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…
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…