In digital online advertising, advertisers procure ad impressions simultaneously on multiple
platforms, or so-called channels, such as Google Ads, Meta Ads Manager, etc., each of …

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 …

In this article, we study the contextual dynamic pricing problem where the market value of a
product is linear in its observed features plus some market noise. Products are sold one at a …

In many online platforms, customers' decisions are substantially influenced by product
rankings as most customers only examine a few top-ranked products. Concurrently, such …

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 …

Contextual dynamic pricing aims to set personalized prices based on sequential interactions
with customers. At each time period, a customer who is interested in purchasing a product …

Today's online advertisers procure digital ad impressions through interacting with
autobidding platforms: advertisers convey high level procurement goals via setting levers …

In the classical contextual bandits problem, in each round $ t $, a learner observes some
context $ c $, chooses some action $ a $ to perform, and receives some reward $ r_ {a, t}(c) …

Dynamic pricing is a fast-moving research area in machine learning and operations
management. A lot of work has been done for this problem with known noise. In this paper …

In a carbon auction, licenses for CO2 emissions are allocated among multiple interested
players. Inspired by this setting, we consider repeated multi-unit auctions with uniform …