1 citations · 3 across the 11 of their papers we have counts for
13 papers
Strategizing against Learners in Bayesian Games
Yishay Mansour, Mehryar Mohri, Jon Schneider +1
We study repeated two-player games where one of the players, the learner, employs a no-regret learning strategy, while the other, the optimizer, is a rational utility maximizer. We…
Price Manipulability in First-Price Auctions
Johannes Brustle, Paul Dütting, Balasubramanian Sivan
First-price auctions have many desirable properties, including uniquely possessing some, like credibility. However, first-price auctions are also inherently non-truthful, and non-t…
Pricing Query Complexity of Revenue Maximization
Renato Paes Leme, Balasubramanian Sivan, Yifeng Teng +1
The common way to optimize auction and pricing systems is to set aside a small fraction of the traffic to run experiments. This leads to the question: how can we learn the most wit…
Approximately Efficient Bilateral Trade
Yuan Deng, Jieming Mao, Balasubramanian Sivan +1
We study bilateral trade between two strategic agents. The celebrated result of Myerson and Satterthwaite states that in general, no incentive-compatible, individually rational and…
Online Allocation and Display Ads Optimization with Surplus Supply
Melika Abolhassani, Hossein Esfandiari, Yasamin Nazari +3
In this work, we study a scenario where a publisher seeks to maximize its total revenue across two sales channels: guaranteed contracts that promise to deliver a certain number of…
Learning to Price Against a Moving Target
Renato Paes Leme, Balasubramanian Sivan, Yifeng Teng +1
In the Learning to Price setting, a seller posts prices over time with the goal of maximizing revenue while learning the buyer's valuation. This problem is very well understood whe…