16 citations · 29 across the 10 of their papers we have counts for
13 papers
Scalable Analysis of Bipartite Experiments
Liang Shi, Edvard Bakhitov, Kenneth Hung +4
Bipartite Experiments are randomized experiments where the treatment is applied to a set of units (randomization units) that is different from the units of analysis, and randomizat…
Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Luofeng Liao, Christian Kroer, Sergei Leonenkov +4
Online A/B testing is widely used in the internet industry to inform decisions on new feature roll-outs. For online marketplaces (such as advertising markets), standard approaches…
Causal clustering: design of cluster experiments under network interference
Davide Viviano, Lihua Lei, Guido Imbens +3
This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers. We provide a framework to choose the clustering…
Multi-Platform Budget Management in Ad Markets with Non-IC Auctions
Fransisca Susan, Negin Golrezaei, Okke Schrijvers
In online advertising markets, budget-constrained advertisers acquire ad placements through repeated bidding in auctions on various platforms. We present a strategy for bidding opt…
Optimal Spend Rate Estimation and Pacing for Ad Campaigns with Budgets
Bhuvesh Kumar, Jamie Morgenstern, Okke Schrijvers
Online ad platforms offer budget management tools for advertisers that aim to maximize the number of conversions given a budget constraint. As the volume of impressions, conversion…
Stochastic Bandits for Multi-platform Budget Optimization in Online Advertising
Vashist Avadhanula, Riccardo Colini-Baldeschi, Stefano Leonardi +2
We study the problem of an online advertising system that wants to optimally spend an advertiser's given budget for a campaign across multiple platforms, without knowing the value…
Equilibria in Auctions With Ad Types
Hadi Elzayn, Riccardo Colini-Baldeschi, Brian Lan +1
This paper studies equilibrium quality of semi-separable position auctions (known as the Ad Types setting) with greedy or optimal allocation combined with generalized second-price…
Envy, Regret, and Social Welfare Loss
Riccardo Colini-Baldeschi, Stefano Leonardi, Okke Schrijvers +1
Incentive compatibility (IC) is one of the most fundamental properties of an auction mechanism, including those used for online advertising. Recent methods by Feng et al. and Lahai…
The Ad Types Problem
Riccardo Colini-Baldeschi, Julián Mestre, Okke Schrijvers +1
The Ad Types Problem (without gap rules) is a special case of the assignment problem in which there are types of nodes on one side (the ads), and an ordered set of nodes on the…
Online Learning for Measuring Incentive Compatibility in Ad Auctions
Zhe Feng, Okke Schrijvers, Eric Sodomka
In this paper we investigate the problem of measuring end-to-end Incentive Compatibility (IC) regret given black-box access to an auction mechanism. Our goal is to 1) compute an es…
Pacing Equilibrium in First-Price Auction Markets
Vincent Conitzer, Christian Kroer, Debmalya Panigrahi +4
Mature internet advertising platforms offer high-level campaign management tools to help advertisers run their campaigns, often abstracting away the intricacies of how each ad is p…
Online Prediction with Selfish Experts
Tim Roughgarden, Okke Schrijvers
We consider the problem of binary prediction with expert advice in settings where experts have agency and seek to maximize their credibility. This paper makes three main contributi…
Ironing in the Dark
Tim Roughgarden, Okke Schrijvers
This paper presents the first polynomial-time algorithm for position and matroid auction environments that learns, from samples from an unknown bounded valuation distribution, an a…