7 citations · 20 across the 14 of their papers we have counts for
15 papers
Competition Complexity in Multi-Item Auctions: Beyond VCG and Regularity
Hedyeh Beyhaghi, Linda Cai, Yiding Feng +2
We quantify the value of the monopoly's bargaining power in terms of competition complexity--that is, the number of additional bidders the monopoly must attract in simple auctions…
Strategic Budget Selection in a Competitive Autobidding World
Yiding Feng, Brendan Lucier, Aleksandrs Slivkins
We study a game played between advertisers in an online ad platform. The platform sells ad impressions by first-price auction and provides autobidding algorithms that optimize bids…
Dynamic Pricing and Advertising with Demand Learning
Shipra Agrawal, Yiding Feng, Wei Tang
We consider a novel pricing and advertising framework in which a seller not only sets the product price but also designs flexible advertising schemes to influence customers' valuat…
Mobility Data in Operations: The Facility Location Problem
Ozan Candogan, Yiding Feng
The recent large scale availability of mobility data, which captures individual mobility patterns, poses novel operational problems that are exciting and challenging. Motivated by…
Batching and Optimal Multi-stage Bipartite Allocations
Yiding Feng, Rad Niazadeh
In several applications of real-time matching of demand to supply in online marketplaces, the platform allows for some latency to batch the demand and improve the efficiency. Motiv…
Two-stage Stochastic Matching and Pricing with Applications to Ride Hailing
Yiding Feng, Rad Niazadeh, Amin Saberi
Matching and pricing are two critical levers in two-sided marketplaces to connect demand and supply. The platform can produce more efficient matching and pricing decisions by batch…
Online Resource Allocation with Cancellations
Farbod Ekbatani, Yiding Feng, Rad Niazadeh
We initiate the study of two-sided online resource allocation with costly cancellations within the buyback model. Our focus is on edge-weighted online matching and several of its e…
Rationality-Robust Information Design: Bayesian Persuasion under Quantal Response
Yiding Feng, Chien-Ju Ho, Wei Tang
Classic mechanism/information design imposes the assumption that agents are fully rational, meaning each of them always selects the action that maximizes her expected utility. Yet…
No-Regret Bayesian Recommendation to Homogeneous Users
Yiding Feng, Wei Tang, Haifeng Xu
We introduce and study the online Bayesian recommendation problem for a recommender system platform. The platform has the privilege to privately observe a utility-relevant \emph{st…
Competitive Information Design for Pandora's Box
Bolin Ding, Yiding Feng, Chien-Ju Ho +2
We study a natural competitive-information-design strategic variant for the celebrated Pandora's Box problem (Weitzman, 1979), where each box is associated with a strategic informa…
Revelation Gap for Pricing from Samples
Yiding Feng, Jason D. Hartline, Yingkai Li
This paper considers prior-independent mechanism design, in which a single mechanism is designed to achieve approximately optimal performance on every prior distribution from a giv…
Selling to Non-linear Agents: A Demand-Based Auction
Yiding Feng, Jason Hartline, Yingkai Li
Auctions allocate scarce goods, from car licenses to online advertising, to buyers whose utilities are often not linear in money, as with budgets or risk aversion. We ask how a sel…
Bias-Variance Games
Yiding Feng, Ronen Gradwohl, Jason Hartline +2
Firms engaged in electronic commerce increasingly rely on predictive analytics via machine-learning algorithms to drive a wide array of managerial decisions. The tuning of many sta…
Optimal Auctions vs. Anonymous Pricing: Beyond Linear Utility
Yiding Feng, Jason D. Hartline, Yingkai Li
The revenue optimal mechanism for selling a single item to agents with independent but non-identically distributed values is complex for agents with linear utility (Myerson,1981) a…
An End-to-end Argument in Mechanism Design (Prior-independent Auctions for Budgeted Agents)
Yiding Feng, Jason D. Hartline
This paper considers prior-independent mechanism design, namely identifying a single mechanism that has near optimal performance on every prior distribution. We show that mechanism…