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We review distributionally robust optimization (DRO), a principled approach for constructing statistical estimators that hedge against the impact of deviations in the expected loss between the training and deployment environments.
Recent advances in algorithmic high-dimensional robust statistics
Diakonikolas, I. and Kane, D. M. (2019) · 1911
Earlier work this paper cites.
A formula for sample sizes for population tolerance limits
Scheffe, H. and Tukey, J. W. (1944) · 1944
Earlier work this paper cites.
Non-parametric estimation. I. Validation of order statistics
Scheffe, H. and Tukey, J. W. (1945) · 1945
Earlier work this paper cites.
Non-normality and tests on variances
Box, G. E. P. (1953) · 1953
Earlier work this paper cites.
On a space of totally additive functions
Kantorovich, L. V. and Rubinshtein, S. (1958) · 1958
Earlier work this paper cites.
A min-max solution of an inventory problem
Scarf, H. (1958) · 1958
Earlier work this paper cites.
Robust covariance and scatter matrix estimation under Huber’s contamination model
Chen, M., Gao, C., and Ren, Z. (2018) · 1960
Earlier work this paper cites.
A survey of sampling from contaminated distributions
Tukey, J. W. (1960) · 1960
Earlier work this paper cites.
The future of data analysis
Tukey, J. W. (1962) · 1962
Earlier work this paper cites.
Convex Functions and Dual Extremum Problems
Rockafellar, R. T. (1963) · 1963
Earlier work this paper cites.
Robust estimation of a location parameter
Huber, P. J. (1964) · 1964
Earlier work this paper cites.
The existence of probability measures with given marginals
Strassen, V. (1965) · 1965
Earlier work this paper cites.
Contributions to the Theory of Robust Estimation
Hampel, F. (1968) · 1968
Earlier work this paper cites.
Robust confidence limits
Huber, P. J. (1968) · 1968
Earlier work this paper cites.
A general qualitative definition of robustness
Hampel, F. R. (1971) · 1971
Earlier work this paper cites.
The 1972 Wald lecture robust statistics: A review
Huber, P. J. (1972) · 1972
Earlier work this paper cites.
Conjugate Duality and Optimization
Rockafellar, R. (1974) · 1974
Earlier work this paper cites.
I-divergence geometry of probability distributions and minimization problems
Csiszár, I. (1975) · 1975
Earlier work this paper cites.
Mathematics and the picturing of data
Tukey, J. W. (1975) · 1975
Earlier work this paper cites.
Science and statistics
Box, G. E. (1976) · 1976
Earlier work this paper cites.
Consistent nonparametric regression
Stone, C. J. (1977) · 1977
Earlier work this paper cites.
The densest hemisphere problem
Johnson, D. and Preparata, F. (1978) · 1978
Earlier work this paper cites.
Robustness in the strategy of scientific model building
Box, G. E. (1979) · 1979
Earlier work this paper cites.
The notion of breakdown point
Donoho, D. L. and Huber, P. J. (1983) · 1983
Earlier work this paper cites.
Extensions of subgradient calculus with applications to optimization
Rockafellar, R. (1985) · 1985
Earlier work this paper cites.
The “automatic” robustness of minimum distance functionals
Donoho, D. L. and Liu, R. C. (1988) · 1988
Earlier work this paper cites.
Potential and kinetic energy in statistics
Székely, G. J. (1989) · 1989
Earlier work this paper cites.
Geometrizing rates of convergence, III
Donoho, D. L. and Liu, R. C. (1991) · 1991
Earlier work this paper cites.
Breakdown properties of location estimates based on halfspace depth and projected outlyingness
Donoho, D. L. and Gasko, M. (1992) · 1992
Earlier work this paper cites.
Statistical Estimation and Optimal Recovery
Donoho, D. L. (1994) · 1994
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · 1996
Earlier work this paper cites.
A decision-theoretic generalization of on-line learning and an application to boosting
Freund, Y. and Schapire, R. E. (1997) · 1997
Earlier work this paper cites.
Convex Analysis
Rockafellar, R. (1997) · 1997
Earlier work this paper cites.
Asymptotic Statistics
Vaart, A. W. v. d. (1998) · 1998
Earlier work this paper cites.
Empirical Likelihood
Owen, A. B. (2001) · 2001
Earlier work this paper cites.
Convex Analysis in General Vector Spaces
Zalinescu, C. (2002) · 2002
Earlier work this paper cites.
Robust Statistics
Huber, P. (2004) · 2004
Earlier work this paper cites.
Feature selection, L 1 L_{1} vs. L 2 L_{2} regularization, and rotational invariance
Ng, A. Y. (2004) · 2004
Earlier work this paper cites.
Robust estimators are hard to compute
Bernholt, T. (2006) · 2005
Earlier work this paper cites.
Optimization of risk measures
Ruszczyński, A. and Shapiro, A. (2006) · 2006
Earlier work this paper cites.
A distributionally robust approach to fair classification
Taskesen, B., Nguyen, V. A., Kuhn, D., and Blanchet, J. (2020) · 2007
Earlier work this paper cites.
Optimal Transport: Old and New
Villani, C. et al. (2009) · 2009
Earlier work this paper cites.
Distributionally robust optimization under moment uncertainty with application to data-driven problems
Delage, E. and Ye, Y. (2010) · 2010
Earlier work this paper cites.
Distributionally robust Markov decision processes
Xu, H. and Mannor, S. (2010) · 2010
Earlier work this paper cites.
Robust linear least squares regression
Audibert, J.-Y. and Catoni, O. (2011) · 2011
Earlier work this paper cites.
Convex Analysis and Monotone Operator Theory in Hilbert Spaces
Bauschke, H. and Combettes, P. (2011) · 2011
Earlier work this paper cites.
Square-root lasso: pivotal recovery of sparse signals via conic programming
Belloni, A., Chernozhukov, V., and Wang, L. (2011) · 2011
Earlier work this paper cites.
Reproducing Kernel Hilbert Spaces in Probability and Statistics
Berlinet, A. and Thomas-Agnan, C. (2011) · 2011
Earlier work this paper cites.
Robust state space filtering under incremental model perturbations subject to a relative entropy tolerance
Levy, B. C. and Nikoukhah, R. (2012) · 2012
Earlier work this paper cites.
Robustness and risk-sensitivity in Markov decision processes
Osogami, T. (2012) · 2012
Earlier work this paper cites.
Kullback-leibler divergence constrained distributionally robust optimization
Hu, Z. and Hong, L. J. (2013) · 2013
Earlier work this paper cites.
Reinforcement learning in robust Markov decision processes
Lim, S. H., Xu, H., and Mannor, S. (2013) · 2013
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014) · 2014
Earlier work this paper cites.
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Goodfellow, I. J., Shlens, J., and Szegedy, C. (2015) · 2015
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A survey of unsupervised deep domain adaptation
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On minimax optimality of gans for robust mean estimation
Wu, K., Ding, G. W., Huang, R., and Yu, Y. (2020) · 2020
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Generalization bounds for (Wasserstein) robust optimization
An, Y. and Gao, R. (2021) · 2021
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Agnostic estimation of mean and covariance
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Robust sensitivity analysis for stochastic systems
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Approximate models and robust decisions
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A survey of transfer learning
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Robust Kalman filtering under model perturbations
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Sensitivity analysis of Wasserstein distributionally robust optimization problems
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Sample out-of-sample inference based on Wasserstein distance
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Statistics of robust optimization: A generalized empirical likelihood approach
Duchi, J. C., Glynn, P. W., and Namkoong, H. (2021) · 2021
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Learning models with uniform performance via distributionally robust optimization
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Higher-order expansion and bartlett correctability of distributionally robust optimization
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Lam, H. (2021) · 2021
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Robustifying conditional portfolio decisions via optimal transport
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Good and bad optimization models: Insights from Rockafellians
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Testing group fairness via optimal transport projections
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A data-driven approach to robust hypothesis testing using kernel mmd uncertainty sets
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Sequential domain adaptation by synthesizing distributionally robust experts
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From data to decisions: Distributionally robust optimization is optimal
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Sinkhorn distributionally robust optimization
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Finite-sample regret bound for distributionally robust offline tabular reinforcement learning
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Kernel distributionally robust optimization: Generalized duality theorem and stochastic approximation
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Estimating processes in adapted Wasserstein distance
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Holistic robust data-driven decisions
Bennouna, A. and Van Parys, B. (2022) · 2022
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Distributionally robust causal inference with observational data
Bertsimas, D., Imai, K., and Li, M. L. (2022) · 2022
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Robust sub-Gaussian estimation of a mean vector in nearly linear time
Depersin, J. and Lecué, G. (2022) · 2022
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Finite-sample guarantees for Wasserstein distributionally robust optimization: Breaking the curse of dimensionality
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Wasserstein distributionally robust optimization and variation regularization
Gao, R., Chen, X., and Kleywegt, A. J. (2022) · 2022
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Tikhonov regularization is optimal transport robust under martingale constraints
Li, J., Lin, S., Blanchet, J., and Nguyen, V. A. (2022) · 2022
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Robust W-GAN-based estimation under Wasserstein contamination
Liu, Z. and Loh, P.-L. (2022) · 2022
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On the generalization error of norm penalty linear regression models
Olea, J. L. M., Rush, C., Velez, A., and Wiesel, J. (2022) · 2022
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Frameworks and results in distributionally robust optimization
Rahimian, H. and Mehrotra, S. (2022) · 2022
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An Optimization Primer
Royset, J. and Wets, R. (2022) · 2022
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Generalized resilience and robust statistics
Zhu, B., Jiao, J., and Steinhardt, J. (2022) · 2022
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Regularization for wasserstein distributionally robust optimization
Azizian, W., Iutzeler, F., and Malick, J. (2023) · 2023
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Bennett, A., Kallus, N., Mao, X., Newey, W., Syrgkanis, V., and Uehara, M. (2023) · 2023
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Statistical limit theorems in distributionally robust optimization
Blanchet, J. and Shapiro, A. (2023) · 2023
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Entropy-regularized wasserstein distributionally robust shape and topology optimization
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Algorithmic High-Dimensional Robust Statistics
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Distributionally robust losses for latent covariate mixtures
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Distributionally robust stochastic optimization with Wasserstein distance
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A data-driven approach to beating SAA out of sample
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A review of deep transfer learning and recent advancements
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Distributionally favorable optimization: A framework for data-driven decision-making with endogenous outliers
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Liu, Z., Van Parys, B. P., and Lam, H. (2023) · 2023
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Wasserstein distributionally robust linear-quadratic estimation under martingale constraints
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Bridging Bayesian and minimax mean square error estimation via Wasserstein distributionally robust optimization
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Distributional robustness, stochastic divergences, and the quadrangle of risk
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Distributionally robust and generalizable inference
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Rockafellian relaxation in optimization under uncertainty: Asymptotically exact formulations
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Shafieezadeh-Abadeh, S., Aolaritei, L., Dörfler, F., and Kuhn, D. (2023) · 2023
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Distributionally robust batch contextual bandits
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On the foundation of distributionally robust reinforcement learning
Wang, S., Si, N., Blanchet, J., and Zhou, Z. (2023) · 2023
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