Fetching the paper…
Reading the bibliography…
Conditional Value-at-Risk ($\mathrm{CV@R}$) is one of the most popular measures of risk, which has been recently considered as a performance criterion in supervised statistical learning, as it is related to desirable operational features in modern applications, such as safety, fairness, distributional robustness, and prediction error stability.
Portfolio Selection
Harry Markowitz · 1952
Earlier work this paper cites.
Gradient Methods for Minimizing Functionals
B. T. Polyak · 1963
Earlier work this paper cites.
Optimization of Conditional Value-at-Risk
R. Tyrrell Rockafellar and Stanislav Uryasev · 2000
Earlier work this paper cites.
New Support Vector Algorithms
Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, and Peter L. Bartlett · 2000
Earlier work this paper cites.
The Nature of Statistical Learning Theory
Vladimir N. Vapnik · 2000
Earlier work this paper cites.
Stochastic Approximation and Recursive Algorithms and Applications
Harold J. (Harold Joseph) Kushner and George Yin · 2003
Earlier work this paper cites.
A Robust Approach Based on Conditional Value-at-Risk Measure to Statistical Learning Problems
Akiko Takeda and Takafumi Kanamori · 2008
Earlier work this paper cites.
ν \nu -Support Vector Machine as Conditional Value-at-Risk Minimization
Akiko Takeda and Masashi Sugiyama · 2008
Earlier work this paper cites.
Lectures on Stochastic Programming: Modeling and Theory
Alexander Shapiro, Darinka Dentcheva, and Andrzej Ruszczyński · 2014
Earlier work this paper cites.
CVaR Minimizations in Support Vector Machines
Jun Ya Gotoh and Akiko Takeda · 2016
Earlier work this paper cites.
Linear Convergence of Gradient and Proximal-Gradient Methods under the Polyak-Łojasiewicz Condition
Hamed Karimi, Julie Nutini, and Mark Schmidt · 2016
Cited alongside, same era.
Risk-Aware Q-learning for Markov Decision Processes
Wenjie Huang and William B. Haskell · 2017
Cited alongside, same era.
Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale
Mehdi Bennis, Merouane Debbah, and H. Vincent Poor · 2018
Cited alongside, same era.
Recursive Optimization of Convex Risk Measures: Mean-Semideviation Models
Dionysios S. Kalogerias and Warren B. Powell · 2018
Cited alongside, same era.
Risk-Averse Access Point Selection in Wireless Communication Networks
Wann-Jiun Ma, Chanwook Oh, Yang Liu, Darinka Dentcheva, and Michael M. Zavlanos · 2018
Cited alongside, same era.
Risk-Averse Classification
Constantine Alexander Vitt, Darinka Dentcheva, and Hui Xiong · 2019
Later among the works it cites.
Fairness Risk Measures
Robert C Williamson and Aditya Krishna Menon · 2019
Later among the works it cites.
Risk-Based Optimization of Virtual Reality over Terahertz Reconfigurable Intelligent Surfaces
Christina Chaccour, Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis, and Petar Popovski · 2020
Closest in time.
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning
Mert Gürbüzbalaban, Andrzej Ruszczyński, and Landi Zhu · 2020
Closest in time.
Learning Bounds for Risk-sensitive Learning
Jaeho Lee, Sejun Park, and Jinwoo Shin · 2020
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Adrian Rivera Cardoso and Huan Xu · 2019
Cited alongside, same era.
Adaptive Sampling for Stochastic Risk-Averse Learning
Sebastian Curi, Kfir. Y. Levy, Stefanie Jegelka, and Andreas Krause · 2019
Cited alongside, same era.
Bi-directional Value Learning for Risk-aware Planning Under Uncertainty
Sung-Kyun Kim, Rohan Thakker, and Ali-akbar Agha-mohammadi · 2019
Cited alongside, same era.
Controlling the Bias-Variance Tradeoff via Coherent Risk for Robust Learning with Kernels
Alec Koppel, Amrit S. Bedi, and Ketan Rajawat · 2019
Cited alongside, same era.
Yan Li, Deke Guo, Yawei Zhao, Xiaofeng Cao, and Honghui Chen · 2020
Closest in time.
PAC-Bayesian Bound for the Conditional Value at Risk
Zakaria Mhammedi, Benjamin Guedj, and Robert C. Williamson · 2020
Closest in time.
Statistical Learning with Conditional Value at Risk
Tasuku Soma and Yuichi Yoshida · 2020
Closest in time.
An Approximation Algorithm for Risk-Averse Submodular Optimization
Lifeng Zhou and Pratap Tokekar · 2020
Closest in time.