A Stochastic Programming Approach for QoS-Aware Service Composition. - Wolfram Wiesemann; Ronald Hochreiter; Daniel Kuhn 001 (CCGRID, 2008)

Bound-based decision rules in multistage stochastic programming. - Daniel Kuhn 001; Panos Parpas; Berç Rustem (Kybernetika, 2008)

A cutting-plane method for Mixed-Logical Semidefinite Programs with an application to multi-vehicle robust path planning. - Fook Wai Kong; Daniel Kuhn 001; Berç Rustem (CDC, 2010)

Maximizing the net present value of a project under uncertainty. - Wolfram Wiesemann; Daniel Kuhn 001; Berç Rustem (Eur. J. Oper. Res., 2010)

Decision rules for information discovery in multi-stage stochastic programming. - Phebe Vayanos; Daniel Kuhn 001; Berç Rustem (CDC/ECC, 2011)

SQPR: Stream query planning with reuse. - Evangelia Kalyvianaki; Wolfram Wiesemann; Quang Hieu Vu; Daniel Kuhn 001; Peter R. Pietzuch (ICDE, 2011)

Robust portfolio optimization with derivative insurance guarantees. - Steve Zymler; Berç Rustem; Daniel Kuhn 001 (Eur. J. Oper. Res., 2011)

Primal and dual linear decision rules in stochastic and robust optimization. - Daniel Kuhn 001; Wolfram Wiesemann; Angelos Georghiou (Math. Program., 2011)

Risk-averse shortest path problems. - Christos Gavriel; Grani Adiwena Hanasusanto; Daniel Kuhn 001 (CDC, 2012)

Multi-resource allocation in stochastic project scheduling. - Wolfram Wiesemann; Daniel Kuhn 001; Berç Rustem (Ann. Oper. Res., 2012)

A constraint sampling approach for multi-stage robust optimization. - Phebe Vayanos; Daniel Kuhn 001; Berç Rustem (Autom., 2012)

Robust Software Partitioning with Multiple Instantiation. - Simon A. Spacey; Wolfram Wiesemann; Daniel Kuhn 001; Wayne Luk (INFORMS J. Comput., 2012)

Improving communication latency with the write-only architecture. - Simon A. Spacey; Wayne Luk; Paul H. J. Kelly; Daniel Kuhn 001 (J. Parallel Distributed Comput., 2012)

Robust resource allocations in temporal networks. - Wolfram Wiesemann; Daniel Kuhn 001; Berç Rustem (Math. Program., 2012)

Robust Data-Driven Dynamic Programming. - Grani Adiwena Hanasusanto; Daniel Kuhn 001 (NIPS, 2013)

Parallel partitioning for distributed systems using sequential assignment. - Simon A. Spacey; Wayne Luk; Daniel Kuhn 001; Paul H. J. Kelly (J. Parallel Distributed Comput., 2013)

Worst-Case Value at Risk of Nonlinear Portfolios. - Steve Zymler; Daniel Kuhn 001; Berç Rustem (Manag. Sci., 2013)

Robust Markov Decision Processes. - Wolfram Wiesemann; Daniel Kuhn 001; Berç Rustem (Math. Oper. Res., 2013)

Distributionally robust joint chance constraints with second-order moment information. - Steve Zymler; Daniel Kuhn 001; Berç Rustem (Math. Program., 2013)

Distributionally Robust Convex Optimization. - Wolfram Wiesemann; Daniel Kuhn 001; Melvyn Sim (Oper. Res., 2014)

Distributionally Robust Logistic Regression. - Soroosh Shafieezadeh-Abadeh; Peyman Mohajerin Esfahani; Daniel Kuhn 001 (NIPS, 2015)

K-Adaptability in Two-Stage Robust Binary Programming. - Grani Adiwena Hanasusanto; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res., 2015)

Interdiction Games on Markovian PERT Networks. - Eli Gutin; Daniel Kuhn 001; Wolfram Wiesemann (Manag. Sci., 2015)

Generalized decision rule approximations for stochastic programming via liftings. - Angelos Georghiou; Wolfram Wiesemann; Daniel Kuhn 001 (Math. Program., 2015)

Distributionally robust multi-item newsvendor problems with multimodal demand distributions. - Grani Adiwena Hanasusanto; Daniel Kuhn 001; Stein W. Wallace; Steve Zymler (Math. Program., 2015)

A distributionally robust perspective on uncertainty quantification and chance constrained programming. - Grani Adiwena Hanasusanto; Vladimir Roitch; Daniel Kuhn 001; Wolfram Wiesemann (Math. Program., 2015)

Financial Optimization: optimization paradigms and financial planning under uncertainty. - Giorgio Consigli; Paolo Brandimarte; Daniel Kuhn 001 (OR Spectr., 2015)

Computational Management Science Special Issue on "Optimisation methods and applications in the energy sector". - Stein-Erik Fleten; Daniel Kuhn 001; Afzal S. Siddiqui (Comput. Manag. Sci., 2016)

Robust Growth-Optimal Portfolios. - Napat Rujeerapaiboon; Daniel Kuhn 001; Wolfram Wiesemann (Manag. Sci., 2016)

A comment on "computational complexity of stochastic programming problems". - Grani Adiwena Hanasusanto; Daniel Kuhn 001; Wolfram Wiesemann (Math. Program., 2016)

Generalized Gauss inequalities via semidefinite programming. - Bart P. G. Van Parys; Paul J. Goulart; Daniel Kuhn 001 (Math. Program., 2016)

K-adaptability in two-stage distributionally robust binary programming. - Grani Adiwena Hanasusanto; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res. Lett., 2016)

Distributionally Robust Control of Constrained Stochastic Systems. - Bart P. G. Van Parys; Daniel Kuhn 001; Paul J. Goulart; Manfred Morari (IEEE Trans. Autom. Control., 2016)

Ambiguous Joint Chance Constraints Under Mean and Dispersion Information. - Grani Adiwena Hanasusanto; Vladimir Roitch; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res., 2017)

On Risk Reduction in Kelly Betting Using the Conservative Expected Value. - Napat Rujeerapaiboon; B. Ross Barmish; Daniel Kuhn 001 (CDC, 2018)

Wasserstein Distributionally Robust Kalman Filtering. - Soroosh Shafieezadeh-Abadeh; Viet Anh Nguyen; Daniel Kuhn 001; Peyman Mohajerin Esfahani (NeurIPS, 2018)

Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls. - Grani Adiwena Hanasusanto; Daniel Kuhn 001 (Oper. Res., 2018)

Chebyshev Inequalities for Products of Random Variables. - Napat Rujeerapaiboon; Daniel Kuhn 001; Wolfram Wiesemann (Math. Oper. Res., 2018)

Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations. - Peyman Mohajerin Esfahani; Daniel Kuhn 001 (Math. Program., 2018)

Data-driven inverse optimization with imperfect information. - Peyman Mohajerin Esfahani; Soroosh Shafieezadeh-Abadeh; Grani Adiwena Hanasusanto; Daniel Kuhn 001 (Math. Program., 2018)

From Infinite to Finite Programs: Explicit Error Bounds with Applications to Approximate Dynamic Programming. - Peyman Mohajerin Esfahani; Tobias Sutter; Daniel Kuhn 001; John Lygeros (SIAM J. Optim., 2018)

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization. - Viet Anh Nguyen; Soroosh Shafieezadeh-Abadeh; Man-Chung Yue; Daniel Kuhn 001; Wolfram Wiesemann (NeurIPS, 2019)

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation. - Viet Anh Nguyen; Soroosh Shafieezadeh-Abadeh; Man-Chung Yue; Daniel Kuhn 001; Wolfram Wiesemann (NeurIPS, 2019)

The decision rule approach to optimization under uncertainty: methodology and applications. - Angelos Georghiou; Daniel Kuhn 001; Wolfram Wiesemann (Comput. Manag. Sci., 2019)

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning. - Daniel Kuhn 001; Peyman Mohajerin Esfahani; Viet Anh Nguyen; Soroosh Shafieezadeh-Abadeh (CoRR, 2019)

Regularization via Mass Transportation. - Soroosh Shafieezadeh-Abadeh; Daniel Kuhn 001; Peyman Mohajerin Esfahani (J. Mach. Learn. Res., 2019)

"Dice"-sion-Making Under Uncertainty: When Can a Random Decision Reduce Risk? - Erick Delage; Daniel Kuhn 001; Wolfram Wiesemann (Manag. Sci., 2019)

Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization. - Napat Rujeerapaiboon; Kilian Schindler; Daniel Kuhn 001; Wolfram Wiesemann (SIAM J. Optim., 2019)

A Distributionally Robust Approach to Fair Classification. - Bahar Taskesen; Viet Anh Nguyen; Daniel Kuhn 001; Jose H. Blanchet (CoRR, 2020)

Distributionally Robust Mechanism Design. - Çagil Koçyigit; Garud Iyengar; Daniel Kuhn 001; Wolfram Wiesemann (Manag. Sci., 2020)

Distributionally robust optimization with polynomial densities: theory, models and algorithms. - Etienne de Klerk; Daniel Kuhn 001; Krzysztof Postek (Math. Program., 2020)

On Topological Equivalence in Linear Quadratic Optimal Control. - Wouter Jongeneel; Daniel Kuhn 001 (ECC, 2021)

A Statistical Test for Probabilistic Fairness. - Bahar Taskesen; Jose H. Blanchet; Daniel Kuhn 001; Viet Anh Nguyen (FAccT, 2021)

Distributionally Robust Optimization with Markovian Data. - Mengmeng Li; Tobias Sutter; Daniel Kuhn 001 (ICML, 2021)

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts. - Bahar Taskesen; Man-Chung Yue; Jose H. Blanchet; Daniel Kuhn 001; Viet Anh Nguyen (ICML, 2021)

Robust Generalization despite Distribution Shift via Minimum Discriminating Information. - Tobias Sutter; Andreas Krause 001; Daniel Kuhn 001 (NeurIPS, 2021)

From Data to Decisions: Distributionally Robust Optimization Is Optimal. - Bart P. G. Van Parys; Peyman Mohajerin Esfahani; Daniel Kuhn 001 (Manag. Sci., 2021)

Energy and reserve dispatch with distributionally robust joint chance constraints. - Christos Ordoudis; Viet Anh Nguyen; Daniel Kuhn 001; Pierre Pinson (Oper. Res. Lett., 2021)

Metrizing Fairness. - Yves Rychener; Bahar Taskesen; Daniel Kuhn 001 (CoRR, 2022)

Topological Linear System Identification via Moderate Deviations Theory. - Wouter Jongeneel; Tobias Sutter; Daniel Kuhn 001 (IEEE Control. Syst. Lett., 2022)

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator. - Viet Anh Nguyen; Daniel Kuhn 001; Peyman Mohajerin Esfahani (Oper. Res., 2022)

Robust multidimensional pricing: separation without regret. - Çagil Koçyigit; Napat Rujeerapaiboon; Daniel Kuhn 001 (Math. Program., 2022)

Scenario reduction revisited: fundamental limits and guarantees. - Napat Rujeerapaiboon; Kilian Schindler; Daniel Kuhn 001; Wolfram Wiesemann (Math. Program., 2022)

On linear optimization over Wasserstein balls. - Man-Chung Yue; Daniel Kuhn 001; Wolfram Wiesemann (Math. Program., 2022)

PIQP: A Proximal Interior-Point Quadratic Programming Solver. - Roland Schwan; Yuning Jiang 002; Daniel Kuhn 001; Colin N. Jones (CDC, 2023)

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective. - Yves Rychener; Daniel Kuhn 001; Tobias Sutter (ICML, 2023)

Contextual Stochastic Bilevel Optimization. - Yifan Hu; Jie Wang 049; Yao Xie 002; Andreas Krause 001; Daniel Kuhn 001 (NeurIPS, 2023)

Distributionally Robust Linear Quadratic Control. - Bahar Taskesen; Dan A. Iancu; Çagil Koçyigit; Daniel Kuhn 001 (NeurIPS, 2023)

New Perspectives on Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization. - Soroosh Shafieezadeh-Abadeh; Liviu Aolaritei; Florian Dörfler; Daniel Kuhn 001 (CoRR, 2023)

Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets. - Mengmeng Li; Tobias Sutter; Daniel Kuhn 001 (CoRR, 2023)

Discrete Optimal Transport with Independent Marginals is #P-Hard. - Bahar Taskesen; Soroosh Shafieezadeh-Abadeh; Daniel Kuhn 001; Karthik Natarajan (SIAM J. Optim., 2023)

Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization. - Viet Anh Nguyen; Soroosh Shafieezadeh-Abadeh; Daniel Kuhn 001; Peyman Mohajerin Esfahani (Math. Oper. Res., 2023)

Semi-discrete optimal transport: hardness, regularization and numerical solution. - Bahar Taskesen; Soroosh Shafieezadeh-Abadeh; Daniel Kuhn 001 (Math. Program., 2023)

On approximations of data-driven chance constrained programs over Wasserstein balls. - Zhi Chen 016; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res. Lett., 2023)

Efficient Learning of a Linear Dynamical System With Stability Guarantees. - Wouter Jongeneel; Tobias Sutter; Daniel Kuhn 001 (IEEE Trans. Autom. Control., 2023)

Stability Verification of Neural Network Controllers Using Mixed-Integer Programming. - Roland Schwan; Colin N. Jones; Daniel Kuhn 001 (IEEE Trans. Autom. Control., 2023)

A large deviations perspective on policy gradient algorithms. - Wouter Jongeneel; Daniel Kuhn 001; Mengmeng Li (L4DC, 2024)

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set. - Man-Chung Yue; Yves Rychener; Daniel Kuhn 001; Viet Anh Nguyen (CoRR, 2024)

Optimism in the Face of Ambiguity Principle for Multi-Armed Bandits. - Mengmeng Li; Daniel Kuhn 001; Bahar Taskesen (CoRR, 2024)

Frequency regulation with storage: On losses and profits. - Dirk Lauinger; François Vuille; Daniel Kuhn 001 (Eur. J. Oper. Res., 2024)

Regret Minimization and Separation in Multi-Bidder, Multi-Item Auctions. - Çagil Koçyigit; Daniel Kuhn 001; Napat Rujeerapaiboon (INFORMS J. Comput., 2024)

Technical Note - Data-Driven Chance Constrained Programs over Wasserstein Balls. - Zhi Chen 016; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res., 2024)

A Planner-Trader Decomposition for Multimarket Hydro Scheduling. - Kilian Schindler; Napat Rujeerapaiboon; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res., 2024)

A Pareto Dominance Principle for Data-Driven Optimization. - Tobias Sutter; Bart P. G. Van Parys; Daniel Kuhn 001 (Oper. Res., 2024)

Reliable Frequency Regulation Through Vehicle-to-Grid: Encoding Legislation with Robust Constraints. - Dirk Lauinger; François Vuille; Daniel Kuhn 001 (Manuf. Serv. Oper. Manag., 2024)

Small Errors in Random Zeroth-Order Optimization Are Imaginary. - Wouter Jongeneel; Man-Chung Yue; Daniel Kuhn 001 (SIAM J. Optim., 2024)

Global Group Fairness in Federated Learning via Function Tracking. - Yves Rychener; Daniel Kuhn 001; Yifan Hu (AISTATS, 2025)

Distributionally robust optimization. - Daniel Kuhn 001; Soroosh Shafiee; Wolfram Wiesemann (Acta Numer., 2025)

A Unified Theory of Robust and Distributionally Robust Optimization via the Primal-Worst-Equals-Dual-Best Principle. - Jianzhe Zhen; Daniel Kuhn 001; Wolfram Wiesemann (Oper. Res., 2025)

Exploiting Multistage Optimization Structure in Proximal Solvers. - Roland Schwan; Daniel Kuhn 001; Colin N. Jones (CoRR, 2025)