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We consider a fundamental problem in microeconomics: selling a single item to a number of potential buyers, whose values are drawn from known independent and regular (not necessarily identical) distributions. There are four widely-used and…

Computer Science and Game Theory · Computer Science 2020-01-23 Yaonan Jin , Pinyan Lu , Zhihao Gavin Tang , Tao Xiao

Optimal transport (OT) provides powerful tools for comparing probability measures in various types. The Wasserstein distance which arises naturally from the idea of OT is widely used in many machine learning applications. Unfortunately,…

Optimization and Control · Mathematics 2021-06-03 Shu Liu , Haodong Sun , Hongyuan Zha

We analyze the revenue loss due to market shrinkage. Specifically, consider a simple market with one item for sale and $n$ bidders whose values are drawn from some joint distribution. Suppose that the market shrinks as a single bidder…

Computer Science and Game Theory · Computer Science 2018-05-30 Shahar Dobzinski , Nitzan Uziely

Multi-item revenue-optimal mechanisms are known to be extremely complex, often offering buyers randomized lotteries of goods. In the standard buy-one model, it is known that optimal mechanisms can yield revenue infinitely higher than that…

Computer Science and Game Theory · Computer Science 2022-11-22 Sepehr Assadi , Vikram Kher , George Li , Ariel Schvartzman

Selling a single item to $n$ self-interested buyers is a fundamental problem in economics, where the two objectives typically considered are welfare maximization and revenue maximization. Since the optimal mechanisms are often impractical…

Computer Science and Game Theory · Computer Science 2024-11-06 Billy Jin , Thomas Kesselheim , Will Ma , Sahil Singla

We address the challenge of sequential data-driven decision-making under context distributional uncertainty. This problem arises in numerous real-world scenarios where the learner optimizes black-box objective functions in the presence of…

Machine Learning · Computer Science 2025-03-27 Francesco Micheli , Efe C. Balta , Anastasios Tsiamis , John Lygeros

In this paper, we consider contextual stochastic optimization problems under endogenous uncertainty, where decisions affect the underlying distributions. To implement such decisions in practice, it is crucial to ensure that their outcomes…

Optimization and Control · Mathematics 2025-10-16 Jasone Ramírez-Ayerbe , Emma Frejinger

We study trade networks with a tree structure, where a seller with a single indivisible good is connected to buyers, each with some value for the good, via a unique path of intermediaries. Agents in the tree make multiplicative revenue…

Computer Science and Game Theory · Computer Science 2013-04-23 Arpita Ghosh , Satyen Kale , Kevin Lang , Benjamin Moseley

Considering two random variables with different laws to which we only have access through finite size iid samples, we address how to reweight the first sample so that its empirical distribution converges towards the true law of the second…

Statistics Theory · Mathematics 2022-06-08 Julien Reygner , Adrien Touboul

The $2$-Wasserstein distance is sensitive to minor geometric differences between distributions, making it a very powerful dissimilarity metric. However, due to this sensitivity, a small outlier mass can also cause a significant increase in…

Machine Learning · Computer Science 2024-06-04 Sharath Raghvendra , Pouyan Shirzadian , Kaiyi Zhang

We consider an auction of identical digital goods to customers whose valuations are drawn independently from known distributions. Myerson's classic result identifies the truthful mechanism that maximizes the seller's expected profit. Under…

Computer Science and Game Theory · Computer Science 2012-04-05 Elchanan Mossel , Omer Tamuz

We provide algorithms that learn simple auctions whose revenue is approximately optimal in multi-item multi-bidder settings, for a wide range of valuations including unit-demand, additive, constrained additive, XOS, and subadditive. We…

Computer Science and Game Theory · Computer Science 2017-09-04 Yang Cai , Constantinos Daskalakis

In this paper, we introduce a Bayesian revenue-maximizing mechanism design model where the items have fixed, exogenously-given prices. Buyers are unit-demand and have an ordinal ranking over purchasing either one of these items at its given…

Computer Science and Game Theory · Computer Science 2020-10-16 Will Ma

We propose to align distributional data from the perspective of Wasserstein means. We raise the problem of regularizing Wasserstein means and propose several terms tailored to tackle different problems. Our formulation is based on the…

Machine Learning · Computer Science 2020-02-24 Liang Mi , Wen Zhang , Yalin Wang

We consider optimal mechanism design for the case with one buyer and two items. The buyer's valuations towards the two items are independent and additive. In this setting, optimal mechanism is unknown for general valuation distributions. We…

Computer Science and Game Theory · Computer Science 2014-04-30 Zihe Wang , Pingzhong Tang

Learning algorithms for implicit generative models can optimize a variety of criteria that measure how the data distribution differs from the implicit model distribution, including the Wasserstein distance, the Energy distance, and the…

Machine Learning · Statistics 2019-08-23 Leon Bottou , Martin Arjovsky , David Lopez-Paz , Maxime Oquab

Sliced Wasserstein distances preserve properties of classic Wasserstein distances while being more scalable for computation and estimation in high dimensions. The goal of this work is to quantify this scalability from three key aspects: (i)…

Machine Learning · Statistics 2022-10-18 Sloan Nietert , Ritwik Sadhu , Ziv Goldfeld , Kengo Kato

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 weakly budget balanced mechanism can be efficient. I.e., no…

Computer Science and Game Theory · Computer Science 2021-11-08 Yuan Deng , Jieming Mao , Balasubramanian Sivan , Kangning Wang

In this work, we aim to reconcile several apparently contradictory observations in market microstructure: is the famous "square-root law" of metaorder impact, which decays with time, compatible with the random-walk nature of prices and the…

Trading and Market Microstructure · Quantitative Finance 2026-03-05 Guillaume Maitrier , Jean-Philippe Bouchaud

We show continuity of the martingale optimal transport optimisation problem as a functional of its marginals. This is achieved via an estimate on the projection in the nested/causal Wasserstein distance of an arbitrary coupling on to the…

Probability · Mathematics 2022-06-22 Johannes Wiesel