![Professor Dirk Kroese](/sites/default/files/profiles/932.jpeg)
Overview
Background
Dirk Kroese's research interests are in: Monte Carlo methods, rare-event simulation, the cross-entropy method, applied probability, and randomised optimisation.
Dirk Kroese is a professor of Mathematics and Statistics at the School of Mathematics and Physics of the University of Queensland. He has held teaching and research positions at The University of Texas at Austin, Princeton University, the University of Twente, the University of Melbourne, and the University of Adelaide. His research interests include Monte Carlo methods, adaptive importance sampling, randomized optimization, and rare-event simulation. He has over 120 peer-reviewed publications, including six monographs:
- Rubinstein, R.Y., Kroese, D.P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning, Springer, New York.
- Rubinstein, R. Y. , Kroese, D. P. (2007). Simulation and the Monte Carlo Method, 2nd edition, John Wiley & Sons.
- Kroese, D.P., Taimre, T., and Botev, Z.I. (2011). Handbook of Monte Carlo Methods, Wiley Series in Probability and Statistics, John Wiley & Sons, New York.
- Kroese, D.P. and Chan, J.C.C. (2014). Statistical Modeling and Computation, Springer, New York.
- Rubinstein, R. Y. , Kroese, D. P. (2017). Simulation and the Monte Carlo Method, 3rd edition, John Wiley & Sons.
- Kroese, D.P., Botev, Z.I., Taimre, T and Vaisman, R. (2019) Data Science and Machine Learning: Mathematical and Statistical Methods, Chapman & Hill/CRC.
- Kroese, D.P. and Botev, Z.I. (2023). An Advanced Course in Probability and Stochastic Processes, Chapman & Hill/CRC.
Availability
- Professor Dirk Kroese is:
- Not available for supervision
- Media expert
Fields of research
Qualifications
- Bachelor of Science, University of Twente
- Masters (Coursework) of Science, University of Twente
- Doctor of Philosophy, University of Twente
Research interests
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The Cross-Entropy Method
The CE methods involves an iterative procedure where each iteration can be broken down into two phases: (a) generate a randon data sample (trajectories, vectors, etc.) according to a specific mechanism; (b) update the parameters of the randdom mechanism based on this data in order to produce a better sample in the next iteration. I am one of the pioneers of the CE method. The simplicity and versatility of the method is explained in my book with R.Y. Rubinstein: The Cross Entropy Method: A Unified Approach to Combinatorial Optimisation. Monte-Carlo Simulation, and Machine Learning, Springer Verlag, 2004. The CE method has been applied to problems in systems reliability, buffer allocation, telecommunication systems, neural computation, control and navigation, DNA sequence alignment, scheduling and many more.
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Monte Carlo Methods
To better understand randomness, it is useful to perform random experiments on a computer. Such "Monte Carlo simulations" are nowadays an essential ingredient in many scientific investigations. Monte Carlo can be used in several different ways: (1) to mimic a random process so as to observe its behaviour, (2) to estimate numerical quantities (e.g., multidimensional integrals) via repeated simulation, and (3) to optimise a complicated (e.g., highly multi-modal) function.
Works
Search Professor Dirk Kroese’s works on UQ eSpace
2024
Journal Article
A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees
Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees. Proceedings of the AAAI Conference on Artificial Intelligence, 38 (18), 20134-20142. doi: 10.1609/aaai.v38i18.29992
2024
Conference Publication
A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees
Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees. 38th AAAI Conference on Artificial Intelligence (AAAI) / 36th Conference on Innovative Applications of Artificial Intelligence / 14th Symposium on Educational Advances in Artificial Intelligence, Vancouver, Canada, 20-27 February 2024. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i18.29992
2023
Book
An advanced course in probability and stochastic processes
Kroese, Dirk P. and Botev, Zdravko I. (2023). An advanced course in probability and stochastic processes. New York, NY United States: Chapman and Hall. doi: 10.1201/9781003315018
2023
Journal Article
Detailed estimation of grid-side current and its oscillations caused by adjustable speed drive systems
Moradi, Arash, Farajizadeh, Farzad, Zare, Firuz, Kumar, Dinesh, Rathnayake, Hansika, Sharma, Rahul and Kroese, Dirk (2023). Detailed estimation of grid-side current and its oscillations caused by adjustable speed drive systems. IEEE Transactions on Industrial Electronics, PP (99), 1-10. doi: 10.1109/tie.2022.3206695
2023
Journal Article
Adaptive discretization using Voronoi trees for continuous pOMDPs
Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2023). Adaptive discretization using Voronoi trees for continuous pOMDPs. The International Journal of Robotics Research. doi: 10.1177/02783649231188984
2023
Journal Article
Model‐based offline reinforcement learning for sustainable fishery management
Ju, Jun, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2023). Model‐based offline reinforcement learning for sustainable fishery management. Expert Systems. doi: 10.1111/exsy.13324
2022
Conference Publication
Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs
Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2022). Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs. Fifteenth Workshop on the Algorithmic Foundations of Robotics WAFR 2022, College Park, MD United States, 22-24 June 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-21090-7_11
2022
Journal Article
Current harmonics generated by multiple adjustable speed drives in distribution networks in the frequency range of 2-9 kHz
Moradi, Arash, Zare, Firuz, Kumar, Dinesh, Yaghoobi, Jalil, Sharma, Rahul and Kroese, Dirk (2022). Current harmonics generated by multiple adjustable speed drives in distribution networks in the frequency range of 2-9 kHz. IEEE Transactions on Industry Applications, 58 (4), 1-1. doi: 10.1109/tia.2022.3172024
2022
Journal Article
Simulating rare events in queues via neural networks
Kroese, Dirk P. and Gibson, Lachlan J. (2022). Simulating rare events in queues via neural networks. Queueing Systems, 100 (3-4), 537-539. doi: 10.1007/s11134-022-09751-0
2022
Book Chapter
Rare-event simulation via neural networks
Gibson, Lachlan J. and Kroese, Dirk P. (2022). Rare-event simulation via neural networks. Advances in Modeling and Simulation. (pp. 151-168) edited by Botev, Zdravko, Lemieux, Christiane, Keller, Alexander and Tuffin, Bruno. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-031-10193-9_8
2021
Conference Publication
Shadow Manifold Hamiltonian Monte Carlo
van der Heide, Chris, Hodgkinson, Liam, Roosta, Fred and Kroese, Dirk (2021). Shadow Manifold Hamiltonian Monte Carlo. International Conference on Artificial Intelligence and Statistics, Online, 27-30- July 2021. Tempe, AZ, United States: ML Research Press.
2021
Conference Publication
Current harmonics generated by multi-power converters in distribution networks in the frequency range of 2-9 kHz
Moradi, Arash, Yaghoobi, Jalil, Zare, Firuz, Kumar, Dinesh, Sharma, Rahul and Kroese, Dirk (2021). Current harmonics generated by multi-power converters in distribution networks in the frequency range of 2-9 kHz. IEEE 19th International Power Electronics and Motion Control Conference (PEMC), Gliwice, Poland, 25-29 April 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/PEMC48073.2021.9432621
2021
Journal Article
Rare events in random geometric graphs
Hirsch, Christian, Moka, Sarat B., Taimre, Thomas and Kroese, Dirk P. (2021). Rare events in random geometric graphs. Methodology and Computing in Applied Probability, 24 (3), 1367-1383. doi: 10.1007/s11009-021-09857-7
2021
Conference Publication
MOOR: Model-based offline reinforcement learning for sustainable fishery management
Ju, Jun, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2021). MOOR: Model-based offline reinforcement learning for sustainable fishery management. 24th International Congress on Modelling and Simulation, Sydney, NSW, Australia, 5 - 10 December 2021. Sydney, NSW, Australia: International Congress on Modelling and Simulation. doi: 10.36334/modsim.2021.M2.ju
2020
Journal Article
Perfect sampling for Gibbs point processes using partial rejection sampling
Moka, Sarat B. and Kroese, Dirk P. (2020). Perfect sampling for Gibbs point processes using partial rejection sampling. Bernoulli, 26 (3), 2082-2104. doi: 10.3150/19-BEJ1184
2020
Journal Article
Chromosome arm aneuploidies shape tumour evolution and drug response
Shukla, Ankit, Nguyen, Thu H. M., Moka, Sarat B., Ellis, Jonathan J., Grady, John P., Oey, Harald, Cristino, Alexandre S., Khanna, Kum Kum, Kroese, Dirk P., Krause, Lutz, Dray, Eloise, Fink, J. Lynn and Duijf, Pascal H. G. (2020). Chromosome arm aneuploidies shape tumour evolution and drug response. Nature Communications, 11 (1) 449, 449. doi: 10.1038/s41467-020-14286-0
2019
Conference Publication
Unbiased estimation of the reciprocal mean for non-negative random variables
Moka, Sarat Babu, Kroese, Dirk P. and Juneja, Sandeep (2019). Unbiased estimation of the reciprocal mean for non-negative random variables. 2019 Winter Simulation Conference (WSC), National Harbor, MD, United States, 8-11 December 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wsc40007.2019.9004815
2019
Book Chapter
Monte Carlo Methods
Taimre, Thomas , Kroese, Dirk P. and Botev, Zdravko I. (2019). Monte Carlo Methods. Wiley StatsRef: Statistics Reference Online. (pp. 1-10) edited by N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri and J. L. Teugels. Hoboken, NJ United States: Wiley-Blackwell. doi: 10.1002/9781118445112.stat03619.pub2
2019
Book
Data science and machine learning: Mathematical and statistical methods
Kroese, Dirk P., Botev, Zdravko I., Taimre, Thomas and Vaisman, Radislav (2019). Data science and machine learning: Mathematical and statistical methods. Boca Raton, FL, United States: CRC Press. doi: 10.1201/9780367816971
2019
Conference Publication
Exact posterior simulation from the linear lasso regression
Botev, Zdravko, Chen, Yi-Lung, L'Ecuyer, Pierre, MacNamara, Shev and Kroese, Dirk P. (2019). Exact posterior simulation from the linear lasso regression. 2018 Winter Simulation Conference, WSC 2018, Gothenburg, Sweden, 9-12 December 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2018.8632237
Funding
Current funding
Supervision
Availability
- Professor Dirk Kroese is:
- Not available for supervision
Supervision history
Current supervision
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Doctor Philosophy
Reinforcement Learning for Large and Complex Partially Observable Markov Decision Processes
Associate Advisor
Other advisors: Dr Nan Ye
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Doctor Philosophy
Statistical Models of Extreme Weather Events in a Changing Climate
Associate Advisor
Other advisors: Dr Meagan Carney
Completed supervision
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2018
Doctor Philosophy
Advances in Monte Carlo Methodology
Principal Advisor
Other advisors: Dr Slava Vaisman, Professor Fred Roosta
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2018
Doctor Philosophy
Optimization by Rare-event Simulation
Principal Advisor
Other advisors: Dr Slava Vaisman
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2017
Doctor Philosophy
Monte Carlo Methods for Discrete Problems
Principal Advisor
Other advisors: Dr Slava Vaisman
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2013
Doctor Philosophy
Markov Chain Monte Carlo for Rare-Event Probability Estimation
Principal Advisor
Other advisors: Dr Ian Wood
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2010
Doctor Philosophy
The generalized splitting method for combinatorial counting and static rare-event probability estimation
Principal Advisor
Other advisors: Professor Joseph Grotowski
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2009
Doctor Philosophy
Parallel and sequential Monte Carlo methods with applications
Principal Advisor
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2009
Doctor Philosophy
Stochastic Modelling and Intervention of the Spread of HIV/AIDS
Principal Advisor
Other advisors: Emeritus Professor Philip Pollett
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2009
Doctor Philosophy
Advances in Cross-Entropy Methods
Principal Advisor
Other advisors: Emeritus Professor Philip Pollett
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2008
Doctor Philosophy
Cross-Entropy Method in Telecommunication Systems
Principal Advisor
Other advisors: Associate Professor Michael Bulmer
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2024
Doctor Philosophy
Active Front End Power Electronics converter: modeling, control and analysis
Associate Advisor
Other advisors: Professor Firuz Zare, Associate Professor Rahul Sharma
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2023
Doctor Philosophy
Newton-MR Methods for Non-convex Smooth Unconstrained Optimizations
Associate Advisor
Other advisors: Professor Fred Roosta
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2023
Doctor Philosophy
Analysis and modelling of harmonics generated by multiple motor drive systems in distribution networks
Associate Advisor
Other advisors: Associate Professor Rahul Sharma, Professor Firuz Zare
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2014
Master Philosophy
Simulation of Stochastic Transport in Complex Systems Using Quantum Techniques
Associate Advisor
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2014
Doctor Philosophy
Estimation of Distribution Algorithms for Single- and Multi-Objective Optimization
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Dr Ian Wood
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2011
Doctor Philosophy
Vehicle and Crew Routing and Scheduling
Associate Advisor
Other advisors: Dr Michael Forbes
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2008
Master Philosophy
TOPICS IN QUASISTATIONARITY FOR MARKOV CHAINS
Associate Advisor
Other advisors: Emeritus Professor Philip Pollett
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2006
Doctor Philosophy
TRIGONOMETRIC SCORES RANK PROCEDURES WITH APPLICATIONS TO LONG-TAILED DISTRIBUTIONS
Associate Advisor
Other advisors: Emeritus Professor Philip Pollett
Media
Enquiries
Contact Professor Dirk Kroese directly for media enquiries about:
- Monte Carlo simulation
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