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We develop a variant of the stochastic prox-linear method for minimizing the Conditional Value-at-Risk (CVaR) objective.
Coherent measures of risk
Philippe Artzner, Freddy Delbaen, Jean-Marc Eber, and David Heath · 1999
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Extreme value theory as a risk management tool
Paul Embrechts, Sidney I. Resnick, and Gennady Samorodnitsky · 1999
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Optimization of Conditional Value-at-Risk
R. Tyrrell Rockafellar and Stanislav Uryasev · 2000
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Credit risk optimization with conditional value-at-risk criterion
Fredrik Andersson, Helmut Mausser, Dan Rosen, and Stanislav Uryasev · 2001
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Portfolio optimization with conditional value-at-risk objective and constraints
Pavlo Krokhmal, Jonas Palmquist, and Stanislav Uryasev · 2002
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Conditional value at risk and related linear programming models for portfolio optimization
Renata Mansini, Wlodzimierz Ogryczak, and Maria Grazia Speranza · 2007
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ν \nu -support vector machine as conditional value-at-risk minimization
Akiko Takeda and Masashi Sugiyama · 2008
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LIBSVM: a library for support vector machines
Chih-Chung Chang and Chih-Jen Lin · 2011
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Risk-Aversion in Multi-armed Bandits
Amir Sani, Alessandro Lazaric, and Rémi Munos · 2012
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Modelling extremal events: for insurance and finance , volume 33
Paul Embrechts, Claudia Klüppelberg, and Thomas Mikosch · 2013
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Algorithms for CVaR Optimization in MDPs
Yinlam Chow and Mohammad Ghavamzadeh · 2014
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Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Yinlam Chow, Aviv Tamar, Shie Mannor, and Marco Pavone · 2015
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Risk averse submodular utility maximization
Takanori Maehara · 2015
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CVaR minimizations in support vector machines
Jun-ya Gotoh and Akiko Takeda · 2016
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A proximal method for composite minimization
Adrian S. Lewis and Stephen J. Wright · 2016
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Minimizing the Maximal Loss: How and Why
Shai Shalev-Shwartz and Yonatan Wexler · 2016
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Stochastic methods for composite and weakly convex optimization problems
John C. Duchi and Feng Ruan · 2018
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Risk-Sensitive Submodular Optimization
Bryan Wilder · 2018
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Risk-Averse Stochastic Convex Bandit
Adrian Rivera Cardoso and Huan Xu · 2019
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Stochastic model-based minimization of weakly convex functions
Damek Davis and Dmitriy Drusvyatskiy · 2019
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Robert C. Williamson and Aditya Krishna Menon · 2019
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Adaptive sampling for stochastic risk-averse learning
Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, and Andreas Krause · 2020
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Amir Beck · 2017
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Risk-Constrained Reinforcement Learning with Percentile Risk Criteria
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Naoto Ohsaka and Yuichi Yoshida · 2017
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John C. Duchi and Hongseok Namkoong · 2018
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The importance of better models in stochastic optimization
Hilal Asi and John C. Duchi
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Stochastic (approximate) proximal point methods: Convergence, optimality, and adaptivity
Hilal Asi and John C. Duchi
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Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization
Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang · 2020
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Statistical learning with conditional value at risk
Tasuku Soma and Yuichi Yoshida · 2020
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Learning with risk-averse feedback under potentially heavy tails
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Cutting some slack for sgd with adaptive polyak stepsizes, 2022
Robert M. Gower, Mathieu Blondel, Nidham Gazagnadou, and Fabian Pedregosa · 2022
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