D. Kuhn

发表

Surveys in Combinatorics 2009: Embedding large subgraphs into dense graphs

D. Kuhn, D. Osthus, Deryk Osthus, 2009, 0901.3541.

Data-Driven Chance Constrained Programs over Wasserstein Balls

D. Kuhn, W. Wiesemann, Zhi Chen, 2018, Operations Research.

Optimal Financial Decision Making Under Uncertainty

D. Kuhn, G. Consigli, P. Brandimarte, 2017 .

Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization pdf

Daniel Kuhn, Peyman Mohajerin Esfahani, Soroosh Shafieezadeh-Abadeh, 2019, Math. Oper. Res..

The Decision Rule Approach to Optimisation under Uncertainty: Methodology and Applications in Operations Management

D. Kuhn, W. Wiesemann, A. Georghiou, 2011 .

Distributionally Robust Logistic Regression

Daniel Kuhn, Peyman Mohajerin Esfahani, Soroosh Shafieezadeh-Abadeh, 2015, NIPS.

Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations

Daniel Kuhn, Peyman Mohajerin Esfahani, D. Kuhn, 2015, Mathematical Programming.

Robust Markov Decision Processes

Daniel Kuhn, Berç Rustem, Wolfram Wiesemann, 2013, Math. Oper. Res..

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Daniel Kuhn, Peyman Mohajerin Esfahani, Viet Anh Nguyen, 2018, Oper. Res..

Scenario reduction revisited: fundamental limits and guarantees

D. Kuhn, W. Wiesemann, Napat Rujeerapaiboon, 2017, Mathematical Programming.

Polynomial Approximations for Continuous Linear Programs

Daniel Kuhn, Dimitra Bampou, D. Kuhn, 2012, SIAM J. Optim..

Threshold Accepting Approach to Improve Bound-based Approximations for Portfolio Optimization

Daniel Kuhn, Berç Rustem, Panos Parpas, 2008 .

Hierarchical , Heterogeneous Control of Non-Linear Dynamical Systems using Reinforcement Learning

D. Kuhn, E. Abramova, A. Faisal, 2012 .

Generalized Bounds for Convex Multistage Stochastic Programs

D. Kuhn, 2004 .

The Stochastic Time-Constrained Net Present Value Problem

D. Kuhn, W. Wiesemann, 2015 .

Hamilton cycles in graphs and hypergraphs: an extremal perspective

D. Kuhn, D. Osthus, Deryk Osthus, 2014, 1402.4268.

Proof of the 1-factorization and Hamilton Decomposition Conjectures

D. Kuhn, D. Osthus, Béla Csaba, 2014, 1401.4183.

A blow-up lemma for approximate decompositions

D. Kuhn, D. Osthus, Jaehoon Kim, 2016, Transactions of the American Mathematical Society.

Analysis of the rebalancing frequency in log-optimal portfolio selection

D. Luenberger, D. Kuhn, 2010 .

Optimal packings of bounded degree trees

D. Kuhn, D. Osthus, Felix Joos, 2016, Journal of the European Mathematical Society.

Resolution of the Oberwolfach problem

D. Kuhn, D. Osthus, Stefan Glock, 2018, Journal of the European Mathematical Society.

University of Birmingham Hamilton decompositions of regular expanders: applications

D. Kuhn, Deryk, 2013 .

Hypergraph $F$-designs for arbitrary $F$

Deryk Osthus, Allan Lo, Stefan Glock, 2017, 1706.01800.

Edge-decompositions of graphs with high minimum degree

D. Kuhn, D. Osthus, A. Lo, 2014, 1410.5750.

Data-driven Inverse Optimization with Incomplete Information

Daniel Kuhn, Peyman Mohajerin Esfahani, Soroosh Shafieezadeh-Abadeh, 2015 .

Dynamic Mean-Variance Portfolio Analysis under Model Risk

Daniel Kuhn, Berç Rustem, Panos Parpas, 2009 .

Semi-discrete optimal transport: hardness, regularization and numerical solution

D. Kuhn, Soroosh Shafieezadeh-Abadeh, Bahar Taskesen, 2021, Mathematical Programming.

On a conjecture of Erd\H{o}s on locally sparse Steiner triple systems

Deryk Osthus, Allan Lo, Stefan Glock, 2018, 1802.04227.

Investigating General Equilibria in Artificial Stock Markets

D. Kuhn, D. Cooke, 2012 .

O C ] 9 M ay 2 01 8 Distributionally robust optimization with polynomial densities : theory , models and algorithms

E. D. Klerk, D. Kuhn, Krzysztof Postek, 2018 .

Barycentric Bounds in Stochastic Programming: Theory and Application

D. Kuhn, K. Frauendorfer, Michael Schürle, 2010 .

New bounds on the size of nearly perfect matchings in almost regular hypergraphs

Dong Yeap Kang, D. Kuhn, D. Osthus, 2020, Journal of the London Mathematical Society.

Robust multidimensional pricing: separation without regret

D. Kuhn, Napat Rujeerapaiboon, Çagil Koçyigit, 2018, Mathematical Programming.

Numerical Methods for Pricing Exotic Options

D. Kuhn, Hardik Dave, 2008 .

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

C. N. Jones, D. Kuhn, Roland Schwan, 2022, ArXiv.

Metrizing Fairness

D. Kuhn, Bahar Taskesen, Yves Rychener, 2022, arXiv.org.

Efficient Learning of a Linear Dynamical System With Stability Guarantees

D. Kuhn, Tobias Sutter, Wouter Jongeneel, 2021, IEEE Transactions on Automatic Control.

Thresholds for Latin squares and Steiner triple systems: Bounds within a logarithmic factor

Dong Yeap Kang, D. Kuhn, D. Osthus, 2022, 2206.14472.

Small errors in random zeroth-order optimization are imaginary

D. Kuhn, Man-Chung Yue, Wouter Jongeneel, 2021, 2103.05478.

Discrete Optimal Transport with Independent Marginals is #P-Hard

D. Kuhn, Soroosh Shafieezadeh-Abadeh, K. Natarajan, 2022, ArXiv.

The decision rule approach to optimization under uncertainty: methodology and applications

D. Kuhn, W. Wiesemann, A. Georghiou, 2018, Computational Management Science.

Scenario reduction revisited: fundamental limits and guarantees

D. Kuhn, W. Wiesemann, Napat Rujeerapaiboon, 2018, Mathematical Programming.

Perfect matchings in random sparsifications of Dirac hypergraphs

Dong Yeap Kang, D. Kuhn, D. Osthus, 2022, 2211.01325.

Distributionally robust optimization with polynomial densities: theory, models and algorithms

D. Kuhn, E. de Klerk, Krzysztof Postek, 2019, Mathematical Programming.

Distributionally Robust Optimal Allocation with Costly Verification

D. Kuhn, M. Pinar, Halil I. Bayrak, 2022, Social Science Research Network.

Generalized decision rule approximations for stochastic programming via liftings

D. Kuhn, W. Wiesemann, A. Georghiou, 2014, Mathematical Programming.

A distributionally robust perspective on uncertainty quantification and chance constrained programming

D. Kuhn, W. Wiesemann, G. A. Hanasusanto, 2015, Mathematical Programming.

Energy Business and Finance Policy - Parallels in Methodology and Duties

D. Kuhn, K. Frauendorfer, Jens Güssow, 2003 .

Generalized Gauss inequalities via semidefinite programming

D. Kuhn, P. Goulart, Bart Van Parys, 2015, Mathematical Programming.

Data-driven inverse optimization with imperfect information

D. Kuhn, Soroosh Shafieezadeh-Abadeh, G. A. Hanasusanto, 2017, Mathematical programming.

Distributionally robust multi-item newsvendor problems with multimodal demand distributions

D. Kuhn, S. Wallace, G. A. Hanasusanto, 2014, Mathematical Programming.

Robust resource allocations in temporal networks

D. Kuhn, W. Wiesemann, B. Rustem, 2011, Mathematical Programming.

Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls

Daniel Kuhn, Grani Adiwena Hanasusanto, D. Kuhn, 2016, Oper. Res..

RLOC: Neurobiologically Inspired Hierarchical Reinforcement Learning Algorithm for Continuous Control of Nonlinear Dynamical Systems pdf

Daniel Kuhn, Luke Dickens, Aldo Faisal, 2019, ArXiv.

Regularization via Mass Transportation

Daniel Kuhn, Peyman Mohajerin Esfahani, Soroosh Shafieezadeh-Abadeh, 2017, J. Mach. Learn. Res..

COMISEF WORKING PAPERS SERIES

Daniel Kuhn, Berç Rustem, Wolfram Wiesemann, 2010 .

Welfare-Maximizing Correlated Equilibria with an Application to Wireless Communication

Fook Wai Kong, D. Kuhn, B. Rustem, 2011 .

A General Framework for Optimal Data-Driven Optimization

Daniel Kuhn, Tobias Sutter, Bart P.G. Van Parys, 2020, 2010.06606.

Robust Growth-Optimal Portfolios

Napat Rujeerapaiboon, Daniel Kuhn, Wolfram Wiesemann, 2016, Manag. Sci..

A Polynomial-Time Solution Scheme for Quadratic Stochastic Programs

Daniel Kuhn, Paula Rocha, D. Kuhn, 2013, Journal of Optimization Theory and Applications.

Worst-Case Value at Risk of Nonlinear Portfolios

Daniel Kuhn, Berç Rustem, Steve Zymler, 2013, Manag. Sci..

Mean-Covariance Robust Risk Measurement

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, 2021, SSRN Electronic Journal.

From Data to Decisions: Distributionally Robust Optimization is Optimal pdf

Daniel Kuhn, Bart P. G. Van Parys, Peyman Mohajerin Esfahani, 2017, Manag. Sci..

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning pdf

Viet Anh Nguyen, Daniel Kuhn, Peyman Mohajerin Esfahani, 2019, Operations Research & Management Science in the Age of Analytics.

Distributionally Robust Convex Optimization

Daniel Kuhn, Wolfram Wiesemann, Melvyn Sim, 2014, Oper. Res..

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation

Wolfram Wiesemann, Viet Anh Nguyen, Daniel Kuhn, 2019, NeurIPS.

Distributionally Robust Optimization with Markovian Data pdf

Daniel Kuhn, Tobias Sutter, Mengmeng Li, 2021, ICML.

SQPR: Stream query planning with reuse

Daniel Kuhn, Wolfram Wiesemann, Peter R. Pietzuch, 2011, 2011 IEEE 27th International Conference on Data Engineering.

Robust Data-Driven Dynamic Programming

Daniel Kuhn, Grani Adiwena Hanasusanto, D. Kuhn, 2013, NIPS.

Wasserstein Distributionally Robust Kalman Filtering

Viet Anh Nguyen, Daniel Kuhn, Peyman Mohajerin Esfahani, 2018, NeurIPS.

A distributionally robust perspective on uncertainty quantification and chance constrained programming

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto, 2015, Mathematical Programming.

Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations

D. Kuhn, Peyman Mohajerin Esfahani, 2017, Mathematical Programming.

Distributionally Robust Control of Constrained Stochastic Systems

Daniel Kuhn, Manfred Morari, Bart P. G. Van Parys, 2016, IEEE Transactions on Automatic Control.

Distributionally robust joint chance constraints with second-order moment information

Daniel Kuhn, Berç Rustem, Steve Zymler, 2011, Mathematical Programming.

Valuation of electricity swing options by multistage stochastic programming

Daniel Kuhn, Gido Haarbrücker, D. Kuhn, 2009, Autom..

Metrizing Fairness

D. Kuhn, Bahar Taskesen, Yves Rychener, 2022, ArXiv.

Robust Generalization despite Distribution Shift via Minimum Discriminating Information pdf

Daniel Kuhn, Andreas Krause, Tobias Sutter, 2021, NeurIPS.

Interdiction Games on Markovian PERT Networks

Daniel Kuhn, Wolfram Wiesemann, Eli Gutin, 2015, Manag. Sci..

Bound-based decision rules in multistage stochastic programming

Daniel Kuhn, Berç Rustem, Panos Parpas, 2008, Kybernetika.

Aggregation and discretization in multistage stochastic programming

Daniel Kuhn, D. Kuhn, 2008, Math. Program..

Scenario-Free Stochastic Programming

Daniel Kuhn, Wolfram Wiesemann, Angelos Georghiou, 2010 .

Primal and dual linear decision rules in stochastic and robust optimization

Daniel Kuhn, Wolfram Wiesemann, Angelos Georghiou, 2011, Math. Program..

Chebyshev Inequalities for Products of Random Variables

Napat Rujeerapaiboon, Daniel Kuhn, Wolfram Wiesemann, 2016, Math. Oper. Res..

A comment on “computational complexity of stochastic programming problems”

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto, 2016, Math. Program..

Mathematical Foundations of Robust and Distributionally Robust Optimization

Daniel Kuhn, Wolfram Wiesemann, Jianzhe Zhen, 2021 .

A Distributionally Robust Approach to Fair Classification pdf

Viet Anh Nguyen, Daniel Kuhn, Bahar Taskesen, 2020, ArXiv.

Convergent Bounds for Stochastic Programs with Expected Value Constraints

Daniel Kuhn, D. Kuhn, 2009 .

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

Wolfram Wiesemann, Viet Anh Nguyen, Daniel Kuhn, 2019, NeurIPS.

Stochastic Optimization of Investment Planning Problems in the Electric Power Industry

Daniel Kuhn, Berç Rustem, Panos Parpas, 2008 .

Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization

Napat Rujeerapaiboon, Daniel Kuhn, Kilian Schindler, 2017, SIAM J. Optim..

Decision rules for information discovery in multi-stage stochastic programming

Daniel Kuhn, Berç Rustem, Phebe Vayanos, 2011, IEEE Conference on Decision and Control and European Control Conference.

On Risk Reduction in Kelly Betting Using the Conservative Expected Value

B. Barmish, D. Kuhn, Napat Rujeerapaiboon, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets

D. Kuhn, Tobias Sutter, Mengmeng Li, 2023, ArXiv.

Distributionally Robust Mechanism Design

G. Iyengar, D. Kuhn, W. Wiesemann, 2017, Manag. Sci..

Multistage stochastic portfolio optimisation in deregulated electricity markets using linear decision rules

Daniel Kuhn, Paula Rocha, D. Kuhn, 2012, Eur. J. Oper. Res..

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Daniel Kuhn, Bahar Taskesen, Jose Blanchet, 2021, ICML.

K-adaptability in two-stage distributionally robust binary programming

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto, 2015, Oper. Res. Lett..

Scenario-free stochastic programming with polynomial decision rules

Daniel Kuhn, Dimitra Bampou, D. Kuhn, 2011, IEEE Conference on Decision and Control and European Control Conference.

Ambiguous Joint Chance Constraints Under Mean and Dispersion Information

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto, 2017, Oper. Res..

A Statistical Test for Probabilistic Fairness pdf

Viet Anh Nguyen, Daniel Kuhn, Bahar Taskesen, 2020, FAccT.

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

D. Kuhn, Tobias Sutter, Yves Rychener, 2023, ICML.

Distributionally robust optimization with polynomial densities: theory, models and algorithms

Daniel Kuhn, Etienne de Klerk, Krzysztof Postek, 2018, Mathematical Programming.

Distributionally robust multi-item newsvendor problems with multimodal demand distributions

Daniel Kuhn, Grani Adiwena Hanasusanto, Stein W. Wallace, 2014, Mathematical Programming.

New Perspectives on Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization

D. Kuhn, F. Dörfler, Soroosh Shafieezadeh-Abadeh, 2023, ArXiv.

Generalized Gauss inequalities via semidefinite programming

Daniel Kuhn, Bart P. G. Van Parys, Paul J. Goulart, 2015, Mathematical Programming.

Regret Minimization and Separation in Multi-Bidder Multi-Item Auctions

Napat Rujeerapaiboon, Daniel Kuhn, Çağıl Koçyiğit, 2020, SSRN Electronic Journal.

Frequency Regulation with Storage: On Losses and Profits

D. Kuhn, Dirk Lauinger, Franccois Vuille, 2023, ArXiv.

On linear optimization over Wasserstein balls

D. Kuhn, Man-Chung Yue, W. Wiesemann, 2020, Mathematical Programming.

Energy and reserve dispatch with distributionally robust joint chance constraints

Daniel Kuhn, Pierre Pinson, Viet Anh Nguyen, 2021, Oper. Res. Lett..

Maximizing the net present value of a project under uncertainty

Daniel Kuhn, Berç Rustem, Wolfram Wiesemann, 2010, Eur. J. Oper. Res..

Small errors in random zeroth-order optimization are imaginary

D. Kuhn, Man-Chung Yue, Wouter Jongeneel, 2021, 2103.05478.

"Dice"-sion-Making Under Uncertainty: When Can a Random Decision Reduce Risk?

Daniel Kuhn, Wolfram Wiesemann, Erick Delage, 2016, Manag. Sci..

The decision rule approach to optimization under uncertainty: methodology and applications

Wolfram Wiesemann, Angelos Georghiou, Daniel Kuhn, 2018, Computational Management Science.

Reliable Frequency Regulation through Vehicle-to-Grid: From EU Legislation to Robust Optimization

Daniel Kuhn, Dirk Lauinger, Franccois Vuille, 2020 .

Reliable Frequency Regulation Through Vehicle-to-Grid: Encoding Legislation with Robust Constraints

D. Kuhn, Dirk Lauinger, Franccois Vuille, 2020, Manufacturing & Service Operations Management.

Combining Markov Decision Processes with Linear Optimal Controllers

Daniel Kuhn, Aldo Faisal, Ekaterina Abramova, 2011, ICCSW.

On approximations of data-driven chance constrained programs over Wasserstein balls

D. Kuhn, W. Wiesemann, Zhi Chen, 2022, Oper. Res. Lett..

Distributionally robust joint chance constraints with second-order moment information

D. Kuhn, B. Rustem, Steve Zymler, 2011, Mathematical Programming.

Generalized decision rule approximations for stochastic programming via liftings

Daniel Kuhn, Wolfram Wiesemann, Angelos Georghiou, 2014, Mathematical Programming.

Data-driven inverse optimization with imperfect information

Daniel Kuhn, Grani Adiwena Hanasusanto, Peyman Mohajerin Esfahani, 2015, Mathematical Programming.

A Planner-Trader Decomposition for Multimarket Hydro Scheduling

D. Kuhn, W. Wiesemann, Napat Rujeerapaiboon, 2021, Operations Research.

The Existence of Designs via Iterative Absorption: Hypergraph 𝐹-designs for Arbitrary 𝐹

D. Kuhn, Stefan Glock, A. Lo, 2016, Memoirs of the American Mathematical Society.

A Unified Theory of Robust and Distributionally Robust Optimization via the Primal-Worst-Equals-Dual-Best Principle

D. Kuhn, W. Wiesemann, Jianzhe Zhen, 2021, Operations Research.

Risk-averse shortest path problems

Daniel Kuhn, Christos Gavriel, Grani Adiwena Hanasusanto, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Robust portfolio optimization with derivative insurance guarantees

Daniel Kuhn, Berç Rustem, Steve Zymler, 2011, Eur. J. Oper. Res..

Thresholds for Latin squares and Steiner triple systems: Bounds within a logarithmic factor

D. Kuhn, T. Kelly, Abhishek Methuku, 2022, 2206.14472.

Efficient Learning of a Linear Dynamical System With Stability Guarantees

D. Kuhn, Tobias Sutter, Wouter Jongeneel, 2021, IEEE Transactions on Automatic Control.

Topological Linear System Identification via Moderate Deviations Theory

D. Kuhn, Tobias Sutter, Wouter Jongeneel, 2021, IEEE Control Systems Letters.

On Topological Equivalence in Linear Quadratic Optimal Control

Daniel Kuhn, Wouter Jongeneel, D. Kuhn, 2021, 2021 European Control Conference (ECC).

Option Pricing with Linear Programming

Napat Rujeerapaiboon, Daniel Kuhn, Panos Parpas, 2012 .

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

D. Kuhn, C. Jones, Roland Schwan, 2022, IEEE Transactions on Automatic Control.

A Stochastic Programming Approach for QoS-Aware Service Composition

Daniel Kuhn, Ronald Hochreiter, Wolfram Wiesemann, 2008, 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGRID).

Analysis of the rebalancing frequency in log-optimal portfolio selection

D. Luenberger, D. Kuhn, 2010 .

Robust resource allocations in temporal networks

Daniel Kuhn, Berç Rustem, Wolfram Wiesemann, 2012, Math. Program..

Dynamic interdiction games on PERT networks

Daniel Kuhn, Wolfram Wiesemann, D. Kuhn, 2012 .

K-Adaptability in Two-Stage Robust Binary Programming

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto, 2015, Oper. Res..

Distributionally Robust Linear Quadratic Control

D. Kuhn, D. Iancu, Çagil Koçyigit, 2023, NeurIPS.

Robust portfolio optimization with derivative insurance guarantees

D. Kuhn, B. Rustem, Steve Zymler, 2011, European Journal of Operational Research.

ICT Enabled Energy Efficiency in Manufacturing

D. Kuhn, K. Ellis, F. Fouchal, 2012 .

PIQP: A Proximal Interior-Point Quadratic Programming Solver

Colin N. Jones, D. Kuhn, Yuning Jiang, 2023, IEEE Conference on Decision and Control.

Generalized decision rule approximations for stochastic programming via liftings

D. Kuhn, W. Wiesemann, A. Georghiou, 2014, Mathematical Programming.

An Information-Based Approximation Scheme for Stochastic Optimization Problems in Continuous Time

Daniel Kuhn, D. Kuhn, 2009, Math. Oper. Res..

Metrizing Fairness

D. Kuhn, Bahar Taşkesen, Yves Rychener, 2022, ArXiv.

A Planner-Trader Decomposition for Multi-Market Hydro Scheduling

D. Kuhn, W. Wiesemann, Napat Rujeerapaiboon, 2021, 2103.02806.