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Learning revenue-maximizing auctions with differentiable matching
We propose a new architecture to approximately learn incentive compatible, revenue-
maximizing auctions from sampled valuations. Our architecture uses the Sinkhorn algorithm …
maximizing auctions from sampled valuations. Our architecture uses the Sinkhorn algorithm …
Platform Equilibrium: Analayzing Social Welfare in Online Market Places
We introduce the theoretical study of a Platform Equilibrium in a market with unit-demand
buyers and unit-supply sellers. Each seller can join a platform and transact with any buyer or …
buyers and unit-supply sellers. Each seller can join a platform and transact with any buyer or …
LLM-Powered Preference Elicitation in Combinatorial Assignment
We study the potential of large language models (LLMs) as proxies for humans to simplify
preference elicitation (PE) in combinatorial assignment. While traditional PE methods rely on …
preference elicitation (PE) in combinatorial assignment. While traditional PE methods rely on …
Learning strong substitutes demand via queries
This article addresses the computational challenges of learning strong substitutes demand
when given access to a demand (or valuation) oracle. Strong substitutes demand …
when given access to a demand (or valuation) oracle. Strong substitutes demand …
The limits of optimal pricing in the dark
A ubiquitous learning problem in today's digital market is, during repeated interactions
between a seller and a buyer, how a seller can gradually learn optimal pricing decisions …
between a seller and a buyer, how a seller can gradually learn optimal pricing decisions …
Recovering utility
We provide sufficient conditions under which a utility function may be recovered from a finite
choice experiment. Identification, as is commonly understood in decision theory, is not …
choice experiment. Identification, as is commonly understood in decision theory, is not …
On the limitations of data‐based price discrimination
The classic third degree price discrimination (3PD) model requires the knowledge of the
distribution of buyer valuations and the covariate to set the price conditioned on the …
distribution of buyer valuations and the covariate to set the price conditioned on the …
[PDF][PDF] Designing and Analyzing Machine Learning Algorithms in the Presence of Strategic Behavior
H Zhang - 2023 - reports-archive.adm.cs.cmu.edu
Abstract Machine learning algorithms now play a major role in all kinds of decision-making
scenarios, such as college admissions, credit approval, and resume screening. When the …
scenarios, such as college admissions, credit approval, and resume screening. When the …
Learning and Robustness with Applications to Mechanism Design
MJ Curry - 2022 - search.proquest.com
The design of economic mechanisms, especially auctions, is an increasingly important part
of the modern economy. A particularly important property for a mechanism is …
of the modern economy. A particularly important property for a mechanism is …
Solving product-mix markets and learning agents' preferences
E Lock - 2021 - ora.ox.ac.uk
This thesis addresses computational questions arising in auctions with multiple goods
available in multiple quantities, with a focus on establishing the tractability of auction …
available in multiple quantities, with a focus on establishing the tractability of auction …