Making the Most of Your Samples

DOI10.1137/16M1065719zbMath1390.91146arXiv1407.2479OpenAlexW2799687852WikidataQ129870200 ScholiaQ129870200MaRDI QIDQ4641589

Tim Roughgarden, Yishay Mansour, Zhi-Yi Huang

Publication date: 18 May 2018

Published in: SIAM Journal on Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1407.2479

zbMATH Keywords

auctionsinformation theorypricingsample complexity

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Auctions, bargaining, bidding and selling, and other market models (91B26)

Related Items (8)

Revenue-Maximizing Auctions: A Bidder’s Standpoint ⋮ Pricing with Samples ⋮ Improved two sample revenue guarantees via mixed-integer linear programming ⋮ A Prior-Independent Revenue-Maximizing Auction for Multiple Additive Bidders ⋮ Making the Most of Your Samples ⋮ Unnamed Item ⋮ On the approximability of simple mechanisms for MHR distributions ⋮ Learning in Repeated Auctions

Cites Work

• Unnamed Item
• Reducing mechanism design to algorithm design via machine learning
• The effectiveness of English auctions.
• Revenue maximization with a single sample
• Competitive auctions
• Mechanism design with approximate valuations
• Vickrey Auctions for Irregular Distributions
• Optimal Selling Strategies under Uncertainty for a Discriminating Monopolist when Demands are Interdependent
• A theory of the learnable
• Making the Most of Your Samples
• Neural Network Learning
• The sample complexity of revenue maximization
• Bayesian Mechanism Design
• How Far Can We Go Beyond Linear Cryptanalysis?
• Optimal and Efficient Parametric Auctions

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