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We consider a generalization of the third degree price discrimination problem studied in Bergemann et al. (2015), where an intermediary between the buyer and the seller can design market segments to maximize any linear combination of…

Computer Science and Game Theory · Computer Science 2019-12-13 Rachel Cummings , Nikhil R. Devanur , Zhiyi Huang , Xiangning Wang

Algorithmic pricing is the computational problem that sellers (e.g., in supermarkets) face when trying to set prices for their items to maximize their profit in the presence of a known demand. Guruswami et al. (2005) propose this problem…

Computer Science and Game Theory · Computer Science 2008-08-13 Shuchi Chawla , Jason Hartline , Robert Kleinberg

Many auction settings implicitly or explicitly require that bidders are treated equally ex-ante. This may be because discrimination is philosophically or legally impermissible, or because it is practically difficult to implement or…

Computer Science and Game Theory · Computer Science 2014-11-06 Christos Tzamos , Christopher A. Wilkens

Randomized mechanisms, which map a set of bids to a probability distribution over outcomes rather than a single outcome, are an important but ill-understood area of computational mechanism design. We investigate the role of randomized…

Computer Science and Game Theory · Computer Science 2009-04-17 Patrick Briest , Shuchi Chawla , Robert Kleinberg , S. Matthew Weinberg

We study markets of indivisible items in which price-based (Walrasian) equilibria often do not exist due to the discrete non-convex setting. Instead we consider Nash equilibria of the market viewed as a game, where players bid for items,…

Computer Science and Game Theory · Computer Science 2011-03-22 Avinatan Hassidim , Haim Kaplan , Yishay Mansour , Noam Nisan

We study single-item single-unit Bayesian posted price auctions, where buyers arrive sequentially and their valuations for the item being sold depend on a random, unknown state of nature. The seller has complete knowledge of the actual…

Computer Science and Game Theory · Computer Science 2022-03-30 Matteo Castiglioni , Giulia Romano , Alberto Marchesi , Nicola Gatti

Optimizing shared vehicle systems (bike/scooter/car/ride-sharing) is more challenging compared to traditional resource allocation settings due to the presence of \emph{complex network externalities} -- changes in the demand/supply at any…

Computer Science and Game Theory · Computer Science 2021-05-12 Siddhartha Banerjee , Daniel Freund , Thodoris Lykouris

Algorithmic decision making systems are ubiquitous across a wide variety of online as well as offline services. These systems rely on complex learning methods and vast amounts of data to optimize the service functionality, satisfaction of…

Machine Learning · Statistics 2017-03-27 Muhammad Bilal Zafar , Isabel Valera , Manuel Gomez Rodriguez , Krishna P. Gummadi

We compare the profit of the optimal third-degree price discrimination policy against a uniform pricing policy. A uniform pricing policy offers the same price to all segments of the market. Our main result establishes that for a broad class…

General Economics · Economics 2021-11-16 Dirk Bergemann , Francisco Castro , Gabriel Weintraub

Budget-feasible procurement has been a major paradigm in mechanism design since its introduction by Singer (2010). An auctioneer (buyer) with a strict budget constraint is interested in buying goods or services from a group of strategic…

Computer Science and Game Theory · Computer Science 2025-05-30 Georgios Amanatidis , Sophie Klumper , Evangelos Markakis , Guido Schäfer , Artem Tsikiridis

Combinatorial Auctions are a central problem in Algorithmic Mechanism Design: pricing and allocating goods to buyers with complex preferences in order to maximize some desired objective (e.g., social welfare, revenue, or profit). The…

Computer Science and Game Theory · Computer Science 2015-03-19 Avrim Blum , Anupam Gupta , Yishay Mansour , Ankit Sharma

Objective prior distributions represent an important tool that allows one to have the advantages of using the Bayesian framework even when information about the parameters of a model is not available. The usual objective approaches work off…

Methodology · Statistics 2018-09-25 Fabrizio Leisen , Cristiano Villa , Stephen G. Walker

Bayesian optimization (BO) is a sample-efficient approach to optimizing costly-to-evaluate black-box functions. Most BO methods ignore how evaluation costs may vary over the optimization domain. However, these costs can be highly…

Machine Learning · Computer Science 2021-11-15 Raul Astudillo , Daniel R. Jiang , Maximilian Balandat , Eytan Bakshy , Peter I. Frazier

This note pursues two primary objectives. First, we analyze the outcomes of an all-pay auction within a store where buyers with and without financial constraints arrive at varying rates, and where buyer types are private information.…

Theoretical Economics · Economics 2024-04-16 Cemil Selcuk

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise.…

Economics · Quantitative Finance 2016-03-01 Pierluigi Gallo , Francesco Randazzo , Ignazio Gallo

Nonconvexities in markets with discrete decisions and nonlinear constraints make efficient pricing challenging, often necessitating subsidies. A prime example is the unit commitment (UC) problem in electricity markets, where costly…

Optimization and Control · Mathematics 2026-02-18 Cheng Guo , Lauren Henderson , Ryan Cory-Wright , Boshi Yang

We consider an online ad network problem in which an ad exchange auctions ad slots and intermediaries called demand side platforms (DSPs) buy these ad slots for their clients (advertisers). An intermediary represents multiple advertisers.…

Computer Science and Game Theory · Computer Science 2019-10-07 Rahul Meshram , Kesav Kaza

This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent, rendering standard approaches…

Econometrics · Economics 2022-06-07 Victor H. Aguiar , Nail Kashaev , Roy Allen

In economics, there are many ways to describe the interaction between a "seller" and a "buyer". The most common one, with which we interact almost every day, is selling for a fixed price. This option is perfect for selling a mass product,…

General Finance · Quantitative Finance 2024-07-10 O. A. Malafeyev , I. E. Khomenko

We consider arbitrage free valuation of European options in Black-Scholes and Merton markets, where the general structure of the market is known, however the specific parameters are not known. In order to reflect this subjective uncertainty…

Mathematical Finance · Quantitative Finance 2017-01-13 Hanno Gottschalk , Elpida Nizami , Marius Schubert
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