WebIncentive-aware Contextual Pricing with Non-parametric Market Noise Negin Golrezaei SloanSchoolofManagement, Massachusetts InstituteofTechnology, … WebKeywords: repeated auctions, learning with strategic agents, incentive-aware learning, pricing 1. Introduction We study the fundamental problem of designing pricing policies for highly heterogeneous items. This study is inspired by the availability of the massive amount of real-time data in online platforms 1
Learning Equilibria in Matching Markets from Bandit Feedback
WebGolrezaei, Jaillet, and Liang: Incentive-aware Contextual Pricing with Non-parametric Market Noise 2 mation about items features/contexts. In such environments, designing optimal policies involves learning buyers’ demand, which is a mapping from item features and offered prices to the likelihood of the item being sold. WebAug 19, 2024 · We design an incentive-aware learning objective that captures the distance of a market outcome from equilibrium. Using this objective, we analyze the complexity of … damaged vocal cords from screaming
Incentive-aware Contextual Pricing with Non-parametric …
WebAug 19, 2024 · We design an incentive-aware learning objective that captures the distance of a market outcome from equilibrium. Using this objective, we analyze the complexity of learning as a function of preference structure, casting learning as a stochastic multi-armed bandit problem. WebOct 14, 2024 · Abstract. Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buyers’ valuations for an item depend on the context that describes the item. However, the seller is not aware of the relationship between the context and ... WebFeb 10, 2024 · Incentive-Aware Machine Learning for Decision Making Watch Via Live Stream As machine learning algorithms are increasingly being deployed for consequential decision making (e.g., loan approvals, college admissions, probation decisions etc.) humans are trying to strategically change the data they feed to these algorithms in an effort to … damaged vs healthy hair