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Exploiting problem structure in optimization under uncertainty via online convex optimization
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Exploiting problem structure in optimization under uncertainty via online convex optimization (2018)Exploiting problem structure in optimizat…Introduction to Online Convex Optimization (2016)Introduction to Online Convex…Introduction to Online Convex Optimization (2016)Introduction to Online Convex…Online Learning with Predictable Sequences (2012)Online Learning with Predicta…Online Learning and Online Convex Optimization (2012)Online Learning and Online Co…Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints (2011)Trading Regret for Efficiency…Theory and Applications of Robust Optimization (2011)Theory and Applications of Ro…Online Learning and Online Convex Optimization (2011)Online Learning and Online Co…Theory and Applications of Robust Optimization (2010)Theory and Applications of Ro…Robust Optimization (2009)Robust OptimizationCutting-set methods for robust convex optimization with pessimizing oracles (2009)Cutting-set methods for robus…Selected topics in robust convex optimization (2007)Selected topics in robust con…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…Robust Portfolio Selection Problems (2003)Robust Portfolio Selection Pr…Online convex programming and generalized infinitesimal gradient ascent (2003)Online convex programming and…Robust optimization ? methodology and applications (2002)Robust optimization ? methodo…Robust Convex Optimization (1998)Robust Convex OptimizationCAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Coherent Measures of Risk (1999)Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems (2010)Introduction to Stochastic Programming (2011)Solving two-stage robust optimization problems using a column-and-constraint generation method (2013)Distributionally Robust Convex Optimization (2014)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Theory of games and economic behavior (2019)Robust solutions of Linear Programming problems contaminated with uncertain data (2000)Robust Solutions of Uncertain Quadratic and Conic-Quadratic Problems (2002)Convex Approximations of Chance Constrained Programs (2006)Facility location under uncertainty: a review (2006)Robust optimization – A comprehensive survey (2007)The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets (1965)THE VALUATION OF RISK ASSETS AND THE SELECTION OF RISKY INVESTMENTS IN STOCK PORTFOLIOS AND CAPITAL BUDGETS**This paper is another in a series of interrelated theoretical and statistical studies of corporate financial and investment policies being made under grants from the Rockefeller Foundation, and more recently the Ford Foundation, to the Harvard Business School. The generous support for this work is most gratefully acknowledged. The author is also much indebted to his colleagues Professors Bishop, Christenson, Kahr, Raiffa, and (especially) Schlaifer, for extensive discussion and commentary on an earlier draft of this paper; but responsibility for any errors or imperfections remains strictly his own.[Professor Sharpe's paper, “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk” (Journal of Finance, September 1964) appeared after this paper was in final form and on its way to the printers. My first section, which parallels the first half of his paper (with corresponding conclusions), sets the algebraic framework for sections II, III and VI, (which have no counterpart in his paper) and for section IV on the equilibrium prices of risk assets, concerning which our results differ significantly for reasons which will be explored elsewhere. Sharpe does not take up the capital budgeting problem developed in section V below.] (1975)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? (2007)Some aspects of the sequential design of experiments (1952)The Nonstochastic Multiarmed Bandit Problem (2002)Big Data Deep Learning: Challenges and Perspectives (2014)A survey of machine learning for big data processing (2016)A survey on deep learning for big data (2017)Robust Optimization of Large-Scale Systems (1995)Robust Discrete Optimization and Its Applications (1997)Robust Discrete Optimization and Its Applications. (1998)The Price of Robustness (2004)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)The Theory of Learning in Games (1998)A Simple Adaptive Procedure Leading to Correlated Equilibrium (2000)Recent advances in robust optimization: An overview (2013)Data-Driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations (2015)Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations (2017)Bandit Algorithms (2020)
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References

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  • 2009Robust Optimization3,008 cited
  • 1998Robust Convex Optimization2,606 cited
  • 2011Theory and Applications of Robust Optimization2,542 cited
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  • 2003Online convex programming and generalized infinitesimal gradient ascent1,789 cited
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  • 2012Online Learning and Online Convex Optimization1,265 cited
  • 2011Online Learning and Online Convex Optimization1,170 cited
  • 2003Robust Portfolio Selection Problems897 cited
  • 2016Introduction to Online Convex Optimization893 cited
  • 2016Introduction to Online Convex Optimization839 cited
  • 2007Selected topics in robust convex optimization363 cited
  • 2009Cutting-set methods for robust convex optimization with pessimizing oracles170 cited
  • 2011Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints168 cited
  • 2012Online Learning with Predictable Sequences159 cited

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