A robust approach based on conditional value-at-risk measure to statistical learning problems

DOI10.1016/j.ejor.2008.07.027zbMath1163.90686OpenAlexW1967249415MaRDI QIDQ1027626

Takafumi Kanamori, Akiko Takeda

Publication date: 30 June 2009

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2008.07.027

zbMATH Keywords

stochastic programmingdata mininguncertainty modellingsupport vector machineconditional value-at-risk

Mathematics Subject Classification ID

Stochastic programming (90C15)

Related Items

Robust ν-support vector machine based on worst-case conditional value-at-risk minimization, Robust Decisions under Risk for Imprecise Probabilities, A stochastic subgradient method for distributionally robust non-convex and non-smooth learning, Nonparametric kernel estimation of expected shortfall under negatively associated sequences, Robust and distributionally robust optimization models for linear support vector machine, Conditional value‐at‐risk beyond finance: a survey, Asymptotic behavior of the empirical conditional value-at-risk, Multi-Loss WCVaR Risk Decision Optimization Based On Weight for Centralized Supply Problem of Direct Chain Enterprises, Realized performance of robust portfolios: worst-case Omega vs. CVaR-related models, Bilevel cutting-plane algorithm for cardinality-constrained mean-CVaR portfolio optimization, Expected shortfall: heuristics and certificates, Tail mean and related robust solution concepts, Nonparametric kernel estimation of CVaR under \(\alpha\)-mixing sequences, Stable portfolio selection strategy for mean-variance-CVaR model under high-dimensional scenarios, Robust portfolio techniques for mitigating the fragility of CVaR minimization and generalization to coherent risk measures, Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs

Uses Software

• SeDuMi
• UCI-ml
• LIBSVM

Cites Work

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