Contextual Search via Intrinsic Volumes

DOI10.1137/20M1385718zbMath1502.90097arXiv1804.03195OpenAlexW2797257208MaRDI QIDQ5092512

Jon Schneider, Renato Paes Leme

Publication date: 22 July 2022

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

Full work available at URL: https://arxiv.org/abs/1804.03195

zbMATH Keywords

online learningintegral geometryconvex geometrypricing algorithms

Mathematics Subject Classification ID

Computational learning theory (68Q32) Management decision making, including multiple objectives (90B50) Microeconomic theory (price theory and economic markets) (91B24)

Cites Work

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• Inequalities between intrinsic volumes
• Computing the volume is difficult
• Close the Gaps: A Learning-While-Doing Algorithm for Single-Product Revenue Management Problems
• Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms
• A random polynomial-time algorithm for approximating the volume of convex bodies
• Bandits with Knapsacks
• Multidimensional Binary Search for Contextual Decision-Making
• Online Decision Making with High-Dimensional Covariates
• Living on the edge: phase transitions in convex programs with random data

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