Algorithmic Aspects of Discrete Choice in Convex Optimization

Müller, David

  • 出版商: Springer Spektrum
  • 出版日期: 2024-11-19
  • 售價: $3,300
  • 貴賓價: 9.5$3,135
  • 語言: 英文
  • 頁數: 133
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 365845704X
  • ISBN-13: 9783658457044
  • 相關分類: Algorithms-data-structures
  • 無法訂購

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商品描述

This book develops a framework to analyze algorithmic aspects of discrete choice models in convex optimization. The central aspect is to derive new prox-functions from discrete choice surplus functions, which are then incorporated into convex optimization schemes. The book provides further economic applications of discrete choice prox-functions within the context of convex optimization such as network manipulation based on alternating minimization and dynamic pricing for online marketplaces.

商品描述(中文翻譯)

本書建立了一個框架,以分析凸優化中離散選擇模型的演算法方面。核心內容是從離散選擇盈餘函數中推導出新的近似函數,然後將其納入凸優化方案中。本書還提供了離散選擇近似函數在凸優化背景下的進一步經濟應用,例如基於交替最小化的網路操作和在線市場的動態定價。

作者簡介

David Müller is a data scientist and former postdoc at the Chair of Business Mathematics at Chemnitz University of Technology. His research focuses on algorithmic and big data aspects of discrete choice models as well as machine learning and non-smooth optimisation.

作者簡介(中文翻譯)

David Müller 是一位數據科學家,曾任職於德國開姆尼茨工業大學商業數學系的博士後研究員。他的研究專注於離散選擇模型的算法和大數據方面,以及機器學習和非光滑優化。