Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Multi-channel autobidding with budget and roi constraints
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 …
platforms, or so-called channels, such as Google Ads, Meta Ads Manager, etc., each of …
A scalable neural network for DSIC affine maximizer auction design
Automated auction design aims to find empirically high-revenue mechanisms through
machine learning. Existing works on multi item auction scenarios can be roughly divided into …
machine learning. Existing works on multi item auction scenarios can be roughly divided into …
Policy optimization using semiparametric models for dynamic pricing
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 …
product is linear in its observed features plus some market noise. Products are sold one at a …
A context-integrated transformer-based neural network for auction design
One of the central problems in auction design is develo** an incentive-compatible
mechanism that maximizes the auctioneer's expected revenue. While theoretical …
mechanism that maximizes the auctioneer's expected revenue. While theoretical …
EdgeDR: An online mechanism design for demand response in edge clouds
The computing frontier is moving from centralized mega datacenters towards distributed
cloudlets at the network edge. We argue that cloudlets are well-suited for handling power …
cloudlets at the network edge. We argue that cloudlets are well-suited for handling power …
Protecting data markets from strategic buyers
The growing adoption of data analytics platforms and machine learning-based solutions for
decision-makers creates a significant demand for datasets, which explains the appearance …
decision-makers creates a significant demand for datasets, which explains the appearance …
Dynamic pricing and learning with bayesian persuasion
We consider a novel dynamic pricing and learning setting where in addition to setting prices
of products in sequential rounds, the seller also ex-ante commits to 'advertising schemes' …
of products in sequential rounds, the seller also ex-ante commits to 'advertising schemes' …
Incentive-aware contextual pricing with non-parametric market noise
We consider a dynamic pricing problem for repeated contextual second-price auctions with
multiple strategic buyers who aim to maximize their long-term time discounted utility. The …
multiple strategic buyers who aim to maximize their long-term time discounted utility. The …
Nash incentive-compatible online mechanism learning via weakly differentially private online learning
We study a multi-round mechanism design problem, where we interact with a set of agents
over a sequence of rounds. We wish to design an incentive-compatible (IC) online learning …
over a sequence of rounds. We wish to design an incentive-compatible (IC) online learning …
Reserve pricing in repeated second-price auctions with strategic bidders
We study revenue optimization learning algorithms for repeated second-price auctions with
reserve where a seller interacts with multiple strategic bidders each of which holds a fixed …
reserve where a seller interacts with multiple strategic bidders each of which holds a fixed …