Robust auction design in the auto-bidding world
In classic auction theory, reserve prices are known to be effective for improving revenue for
the auctioneer against quasi-linear utility maximizing bidders. The introduction of reserve …
the auctioneer against quasi-linear utility maximizing bidders. The introduction of reserve …
A unifying framework for online optimization with long-term constraints
We study online learning problems in which a decision maker has to take a sequence of
decisions subject to $ m $ long-term constraints. The goal of the decision maker is to …
decisions subject to $ m $ long-term constraints. The goal of the decision maker is to …
The landscape of auto-bidding auctions: Value versus utility maximization
Internet advertisers are increasingly adopting automated bidders to buy advertising
opportunities. Automated bidders simplify the procurement process by allowing advertisers …
opportunities. Automated bidders simplify the procurement process by allowing advertisers …
Autobidders with budget and roi constraints: Efficiency, regret, and pacing dynamics
We study a game between autobidding algorithms that compete in an online advertising
platform. Each autobidder is tasked with maximizing its advertiser's total value over multiple …
platform. Each autobidder is tasked with maximizing its advertiser's total value over multiple …
Auction design in an auto-bidding setting: Randomization improves efficiency beyond vcg
A Mehta - Proceedings of the ACM Web Conference 2022, 2022 - dl.acm.org
Auto-bidding is an area of increasing importance in the domain of online advertising. We
study the problem of designing auctions in an auto-bidding setting with the goal of …
study the problem of designing auctions in an auto-bidding setting with the goal of …
Contextual bandits with packing and covering constraints: A modular lagrangian approach via regression
A Slivkins, KA Sankararaman… - The Thirty Sixth Annual …, 2023 - proceedings.mlr.press
We consider contextual bandits with linear constraints (CBwLC), a variant of contextual
bandits in which the algorithm consumes multiple resources subject to linear constraints on …
bandits in which the algorithm consumes multiple resources subject to linear constraints on …
[PDF][PDF] Bidding and pricing in budget and roi constrained markets
In online advertising markets, setting budget and return on investment (ROI) constraints are
two prevalent ways to help advertisers (ie buyers) utilize limited monetary resources …
two prevalent ways to help advertisers (ie buyers) utilize limited monetary resources …
Gender preferences in job vacancies and workplace gender diversity
Abstract In Spring 2005, the Ombud for Equal Treatment in Austria launched a campaign
notifying employers and newspapers that gender preferences in job ads were illegal. At the …
notifying employers and newspapers that gender preferences in job ads were illegal. At the …
Online Learning under Budget and ROI Constraints via Weak Adaptivity
We study online learning problems in which a decision maker has to make a sequence of
costly decisions, with the goal of maximizing their expected reward while adhering to budget …
costly decisions, with the goal of maximizing their expected reward while adhering to budget …
[PDF][PDF] Fairness in the autobidding world with machine-learned advice
The increasing availability of real-time data has fueled the prevalence of algorithmic bidding
(or autobidding) in online advertising markets, and has enabled online ad platforms to …
(or autobidding) in online advertising markets, and has enabled online ad platforms to …