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:
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
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
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
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries
(2020–2023) ARC Discovery Projects
High Quality and Robust Energy Conversion Systems for Distribution Networks
(2018–2021) ARC Linkage Projects
Large Scale Sequential Decision Making in an Uncertain World.
(2017–2019) Office of Naval Research, Dept of the Navy, USA
Decision Making In An Uncertain World
(2019) Doctor Philosophy
Sequential Monte Carlo for Random Graphs
(2019) Master Philosophy
Advances in Monte Carlo Methodology
(2018) Doctor Philosophy
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.
Simulation and the Monte Carlo method
Rubinstein, Reuven Y. and Kroese, Dirk P. (2017). Simulation and the Monte Carlo method. 3rd ed. Hoboken, NJ, United States: John Wiley and Sons. doi: 10.1002/9781118631980
Statistical Modeling and Computation
Kroese, Dirk P. and Chan, Joshua C. C. (2014). Statistical Modeling and Computation. New York, NY, United States: Springer New York. doi: 10.1007/978-1-4614-8775-3
Handbook of Monte Carlo Methods
Kroese, Dirk P., Taimre, Thomas and Botev, Zdravko I. (2011). Handbook of Monte Carlo Methods. Hoboken, NJ, U.S.A.: John Wiley & Sons. doi: 10.1002/9781118014967
Simulation and the Monte Carlo Method
Rubinstein, Reuven Y. and Kroese, Dirk P. (2008). Simulation and the Monte Carlo Method. 2nd ed. New York, United States: John Wiley & Sons. doi: 10.1002/9780470230381
Simulation and the Monte Carlo Method: Solutions Manual to Accompany
Kroese, Dirk P., Taimre, Thomas, Botev, Zdravko I. and Rubinstein, Rueven Y. (2007). Simulation and the Monte Carlo Method: Solutions Manual to Accompany. Hoboken, NJ, United States: John Wiley & Sons. doi: 10.1002/9780470285312
Solutions manual to accompany simulation and the Monte Carlo Method
Kroese, Dirk P., Taimre, Thomas, Botev, Zdravko I. and Rubinstein, Reuven Y. (2007). Solutions manual to accompany simulation and the Monte Carlo Method. 2nd ed. Hoboken, N.J., U.S.A.: Wiley-Interscience.
Rubinstein, R.Y. and Kroese, D. P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning. New York: Springer.
Kroese, Dirk P., Rubinstein, Reuven Y., Cohen, Izack, Porotsky, Sergey and Taimre, Thomas (2013). Cross-entropy method. Encyclopedia of operations research and management science. (pp. 326-333) edited by Saul I. Gass and Michael C. Fu. New York, United States: Springer. doi: 10.1007/978-1-4419-1153-7_131
Monte Carlo methods for portfolio credit risk
Brereton, Tim J., Kroese, Dirk P. and Chan, Joshua C. (2013). Monte Carlo methods for portfolio credit risk. Credit securitisations and derivatives: challenges for the global markets. (pp. 127-152) edited by Daniel Rösch and Harald Scheule. Chicester, United Kingdom: John Wiley & Sons.
The cross-entropy method for estimation
Kroese, Dirk P., Rubinstein, Reuven Y. and Glynn, Peter W. (2013). The cross-entropy method for estimation. Machine learning: theory and applications. (pp. 19-34) edited by Venu Govindaraju and C. R. Rao. Dordrecht, Netherlands: Elsevier. doi: 10.1016/B978-0-444-53859-8.00002-3
The cross-entropy method for optimization
Botev, Zdravko, I., Kroese, Dirk P., Rubinstein, Reuven Y. and L'Ecuyer, Pierre (2013). The cross-entropy method for optimization. Machine learning: theory and applications. (pp. 35-59) edited by Venu Govindaraju and C. R. Rao. Dordrecht, Netherlands: Elsevier. doi: 10.1016/B978-0-444-53859-8.00003-5
Kroese, Dirk P. (2010). Cross-entropy method. Encyclopedia of operations research and management sciences. (pp. 1-12) New York, United States: Springer-Verlag. doi: 10.1002/9780470400531.eorms0210
Applications of the cross-entropy method in reliability
Kroese, D. P. and Hui, Kin-Ping (2007). Applications of the cross-entropy method in reliability. Computational intelligence in reliability engineering. New metaheuristics, neural and fuzzy techniques in reliability. (pp. 37-82) edited by Gregory Levitin. Berlin, Germany: Springer-Verlag. doi: 10.1007/978-3-540-37372-8_3
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
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
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
On the analysis of independent sets via multilevel splitting
Vaisman, Radislav and Kroese, Dirk P. (2018). On the analysis of independent sets via multilevel splitting. Networks, 71 (3), 281-301. doi: 10.1002/net.21805
Splitting for Multi-objective Optimization
Duan, Qibin and Kroese, Dirk P. (2017). Splitting for Multi-objective Optimization. Methodology and Computing in Applied Probability, 20 (2), 517-533. doi: 10.1007/s11009-017-9572-5
Without-replacement sampling for particle methods on finite state spaces
Shah, Rohan and Kroese, Dirk P. (2017). Without-replacement sampling for particle methods on finite state spaces. Statistics and Computing, 28 (3), 1-20. doi: 10.1007/s11222-017-9752-8
The Multilevel Splitting algorithm for graph colouring with application to the Potts model
Vaisman, Radislav, Roughan, Matthew and Kroese, Dirk P. (2017). The Multilevel Splitting algorithm for graph colouring with application to the Potts model. Philosophical Magazine, 97 (19), 1646-1673. doi: 10.1080/14786435.2017.1312023
CEoptim: cross-entropy R package for optimization
Benham, Tim, Duan, Qibin, Kroese, Dirk P. and Liquet, Benoît (2017). CEoptim: cross-entropy R package for optimization. Journal of Statistical Software, 76 (1), 1-29. doi: 10.18637/jss.v076.i08
Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks
Vaisman, Radislav, Kroese, Dirk P. and Gertsbakh, Ilya B. (2016). Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks. Structural Safety, 63, 1-10. doi: 10.1016/j.strusafe.2016.07.001
Duan, Qibin and Kroese, Dirk P. (2016). Splitting for optimization. Computers and Operations Research, 73, 119-131. doi: 10.1016/j.cor.2016.04.015
A comparison of random walks in dependent random environments
Scheinhardt, Werner R. W. and Kroese, Dirk P. (2016). A comparison of random walks in dependent random environments. Advances in Applied Probability, 48 (1), 199-214. doi: 10.1017/apr.2015.13
Improved sampling plans for combinatorial invariants of coherent systems
Vaisman, Radislav, Kroese, Dirk P. and Gertsbakh, Ilya B. (2016). Improved sampling plans for combinatorial invariants of coherent systems. IEEE Transactions on Reliability, 65 (1) 7161416, 410-424. doi: 10.1109/TR.2015.2446471
Fitting Laguerre tessellation approximations to tomographic image data
Spettl, A., Brereton, T., Duan, Q., Werz, T., Krill, C. E., Kroese, D. P. and Schmidt, V. (2016). Fitting Laguerre tessellation approximations to tomographic image data. Philosophical Magazine, 96 (2), 166-189. doi: 10.1080/14786435.2015.1125540
Stochastic Enumeration Method for Counting Trees
Vaisman, Radislav and Kroese, Dirk P (2015). Stochastic Enumeration Method for Counting Trees. Methodology and Computing in Applied Probability, 19 (1), 31-73. doi: 10.1007/s11009-015-9457-4
Westhoff, D., Van Franeker, J. J., Brereton, T., Kroese, D. P., Janssen, R. A. J. and Schmidt, V. (2015). Stochastic modeling and predictive simulations for the microstructure of organic semiconductor films processed with different spin coating velocities. Modelling and Simulation in Materials Science and Engineering, 23 (4) 045003, 1-21. doi: 10.1088/0965-0393/23/4/045003
Kroese, Dirk P and Botev, Zdravko I (2015). Spatial process simulation. Lecture Notes in Mathematics, 2120, 369-404. doi: 10.1007/978-3-319-10064-7_12
A critical exponent for shortest-path scaling in continuum percolation
Brereton, Tim, Hirsch, Christian, Schmidt, Volker and Kroese, Dirk (2014). A critical exponent for shortest-path scaling in continuum percolation. Journal of Physics A: Mathematical and Theoretical, 47 (50) 505003, 1-12. doi: 10.1088/1751-8113/47/50/505003
Grace, Adam W., Kroese, Dirk P. and Sandmann, Werner (2014). Automated state-dependent importance sampling for Markov jump processes via sampling from the zero-variance distribution. Journal of Applied Probability, 51 (3), 741-755. doi: 10.1239/jap/1409932671
Inverting Laguerre tessellations
Duan, Qibin, Kroese, Dirk P., Brereton, Tim, Spettl, Aaron and Schmidt, Volker (2014). Inverting Laguerre tessellations. The Computer Journal, 57 (9), 1431-1440. doi: 10.1093/comjnl/bxu029
Why the Monte Carlo method is so important today
Kroese, Dirk P., Brereton, Tim, Taimre, Thomas and Botev, Zdravko I. (2014). Why the Monte Carlo method is so important today. Wiley Interdisciplinary Reviews: Computational Statistics, 6 (6), 386-392. doi: 10.1002/wics.1314
Efficient simulation of Markov chains using segmentation
Brereton, Tim, Stenzel, Ole, Baumeier, Bjorn, Andrienko, Denis, Schmidt, Volker and Kroese, Dirk (2014). Efficient simulation of Markov chains using segmentation. Methodology and Computing in Applied Probability, 16 (2), 465-484. doi: 10.1007/s11009-013-9327-x
Stenzel, Ole, Hirsch, Christian, Brereton, Tim, Baumeier, Bjoern, Andrienko, Denis, Kroese, Dirk and Schmidt, Volker (2014). A general framework for consistent estimation of charge transport properties via random walks in random environments. Multiscale Modeling and Simulation, 12 (3), 1108-1134. doi: 10.1137/130942504
Graph-based simulated annealing: a hybrid approach to stochastic modeling of complex microstructures
Stenzel, O., Westhoff, D., Manke, I., Kasper, M., Kroese, D. P. and Schmidt, V. (2013). Graph-based simulated annealing: a hybrid approach to stochastic modeling of complex microstructures. Modelling and Simulation in Materials Science and Engineering, 21 (5) 055004, 055004.1-055004.18. doi: 10.1088/0965-0393/21/5/055004
Efficient Monte Carlo simulation via the generalized splitting method
Botev, Zdravko I. and Kroese, Dirk P. (2012). Efficient Monte Carlo simulation via the generalized splitting method. Statistics and Computing, 22 (1), 171-16. doi: 10.1007/s11222-010-9201-4
Improved cross-entropy method for estimation
Chan, Joshua C.C. and Kroese, Dirk P. (2012). Improved cross-entropy method for estimation. Statistics and Computing, 22 (5), 1031-1040. doi: 10.1007/s11222-011-9275-7
Kroese, Dirk P. and Rubinstein, Reuven Y. (2012). Monte Carlo methods. Wiley Interdisciplinary Reviews: Computational Statistics, 4 (1), 48-58. doi: 10.1002/wics.194
Rare-event probability estimation with conditional Monte Carlo
Chan, Joshua C. C. and Kroese, Dirk P. (2011). Rare-event probability estimation with conditional Monte Carlo. Annals of Operations Research, 189 (1), 43-61. doi: 10.1007/s10479-009-0539-y
Kroese, Dirk, Shimkin, Namhum, Kreimer, Joseph and Juneja, Sandeep (2011). Preface. Annals of Operations Research, 189 (1), 1-3. doi: 10.1007/s10479-010-0745-7
Stability and performance of greedy server systems: A review and open problems
Rojas-Nandayapa, Leonardo, Foss, Sergey and Kroese, Dirk P. (2011). Stability and performance of greedy server systems: A review and open problems. Queueing Systems: Theory and Applications, 68 (3-4), 221-227. doi: 10.1007/s11134-011-9235-0
The generalized cross entropy method, with applications to probability density estimation
Botev, Zdravko I. and Kroese, Dirk P. (2011). The generalized cross entropy method, with applications to probability density estimation. Methodology and Computing in Applied Probability, 13 (1), 1-27. doi: 10.1007/s11009-009-9133-7
A comparison of cross-entropy and variance minimization strategies
Chan, Joshua. C., Glynn, Peter W. and Kroese, Dirk P. (2011). A comparison of cross-entropy and variance minimization strategies. Journal of Applied Probability, 48 A (A), 1-15. doi: 10.1239/jap/1318940464
Estimating change-points in biological sequences via the cross-entropy method
Evans, G. E., Sofronov, G. Y., Keith, J. M. and Kroese, D. P. (2011). Estimating change-points in biological sequences via the cross-entropy method. Annals of Operations Research, 189 (1), 155-165. doi: 10.1007/s10479-010-0687-0
Kernel density estimation via diffusion
Botev, Z. I., Grotowski, J. F. and Kroese, D. P. (2010). Kernel density estimation via diffusion. Annals of Statistics, 38 (5), 2916-2957. doi: 10.1214/10-AOS799
Efficient estimation of large portfolio loss probabilities in t-copula models
Chan, Joshua C. C. and Kroese, Dirk P. (2010). Efficient estimation of large portfolio loss probabilities in t-copula models. European Journal of Operational Research, 205 (2), 361-367. doi: 10.1016/j.ejor.2010.01.003
Identifying Change-Points in Biological Sequences via Sequential Importance Sampling
Sofronov, George Yu., Evans, Gareth E., Keith, Jonathan M. and Kroese, Dirk P (2009). Identifying Change-Points in Biological Sequences via Sequential Importance Sampling. Environmental Modeling & Assessment, 14 (5), 577-584. doi: 10.1007/s10666-008-9160-8
Adaptive independence samplers
Keith, J. M., Kroese, D. P. and Sofronov, G. Y. (2008). Adaptive independence samplers. Statistics and Computing, 18 (4), 409-420. doi: 10.1007/s11222-008-9070-2
Botev, Z. I. and Kroese, D. P. (2008). An efficient algorithm for rare-event probability estimation, combinatorial optimization, and counting. Methodology And Computing In Applied Probability, 10 (4), 471-505. doi: 10.1007/s11009-008-9073-7
Controlling the number of HIV infectives in a mobile population
Sani, A. and Kroese, D. P. (2008). Controlling the number of HIV infectives in a mobile population. Mathematical Biosciences, 213 (2), 103-112. doi: 10.1016/j.mbs.2008.03.003
Non-asymptotic bandwidth selection for density estimation of discrete data
Botev, Z. I. and Kroese, D. P. (2008). Non-asymptotic bandwidth selection for density estimation of discrete data. Methodology And Computing In Applied Probability, 10 (3), 435-451. doi: 10.1007/s11009-007-9057-z
Truck fleet model for design and assessment of flexible pavements
Belay, A., O'Brien, E. and Kroese, D. P. (2008). Truck fleet model for design and assessment of flexible pavements. Journal of Sound and Vibration, 311 (3-5), 1161-1174. doi: 10.1016/j.jsv.2007.10.019
Applications of the cross-entropy method in reliability
Kroese, Dirk P. and Hui, Kin-Ping (2007). Applications of the cross-entropy method in reliability. Studies in Computational Intelligence, 40, 37-82. doi: 10.1007/978-3-540-37372-8_3
Application of the cross-entropy method to clustering and vector quantization
Kroese, Dirk P., Rubinstein, Reuven Y. and Taimre, Thomas (2007). Application of the cross-entropy method to clustering and vector quantization. Journal of Global Optimization, 37 (1), 137-157. doi: 10.1007/s10898-006-9041-0
Convergence properties of the cross-entropy method for discrete optimization
Costa, A., Jones, O. D. and Kroese, D. P. (2007). Convergence properties of the cross-entropy method for discrete optimization. Operations Research Letters, 35 (5), 573-580. doi: 10.1016/j.orl.2006.11.005
Estimating the number of s-t paths in a graph
Roberts, B. and Kroese, D. P. (2007). Estimating the number of s-t paths in a graph. Journal of Graph Algorithms and Applications, 11 (1), 195-214. doi: 10.7155/jgaa.00142
Generalized cross-entropy methods with applications to rare-event simulation and optimization
Botev, Z. I., Kroese, D. P. and Taimre, T. (2007). Generalized cross-entropy methods with applications to rare-event simulation and optimization. Simulation, 83 (11), 785-806. doi: 10.1177/0037549707087067
Network reliability optimization via the cross-entropy method
Kroese, D. P., Hui, K. P. and Nariai, S. (2007). Network reliability optimization via the cross-entropy method. IEEE Transactions on Reliability, 56 (2), 275-287. doi: 10.1109/TR.2007.895303
Stochastic models for the spread of HIV in a mobile heterosexual population
Sani, A., Kroese, D. P. and Pollett, P. K. (2007). Stochastic models for the spread of HIV in a mobile heterosexual population. Mathematical Biosciences, 208 (1), 98-124. doi: 10.1016/j.mbs.2006.09.024
An optimal sequential procedure for a buying-selling problem with independent observations
Sofronov, G, Keith, JM and Kroese, DP (2006). An optimal sequential procedure for a buying-selling problem with independent observations. Journal of Applied Probability, 43 (2), 454-462. doi: 10.1239/jap/1152413734
Improved algorithms for rare event simulation with heavy tails
Asmussen, Søren and Kroese, Dirk P. (2006). Improved algorithms for rare event simulation with heavy tails. Advances In Applied Probability, 38 (2), 545-558. doi: 10.1239/aap/1151337084
The cross-entropy method for continuous multi-extremal optimization
Kroese, Dirk P., Porotsky, Sergey and Rubinstein, Reuven Y. (2006). The cross-entropy method for continuous multi-extremal optimization. Methodology and Computing In Applied Probability, 8 (3), 383-407. doi: 10.1007/s11009-006-9753-0
A tutorial on the cross-entropy method
De Boer, Pieter-Tjerk, Kroese, Dirk P., Mannor, Shie and Rubinstein, Reuven Y. (2005). A tutorial on the cross-entropy method. Annals of Operations Research, 134 (1), 19-67. doi: 10.1007/s10479-005-5724-z
Alon, G., Kroese, D. P., Raviv, T. and Rubinstein, R. Y. (2005). Application of the cross-entropy method to the buffer allocation problem in a simulation-based environment. Annals of Operations Research, 134 (1), 137-151. doi: 10.1007/s10479-005-5728-8
Heavy tails, importance sampling and cross-entropy
Asmussen, S., Kroese, D. P. and Rubinstein, R. Y. (2005). Heavy tails, importance sampling and cross-entropy. Stochastic Models, 21 (1), 57-76. doi: 10.1081/STM-200046472
Kroese, Dirk P. and Rubinstein, Reuvem Y. (2005). Preface : From the issue entitled "The Cross-Entropy Method for Combinatorial Optimization, Rare Event Simulation and Neural Computation". Annals of Operations Research, 134 (1), 17-18. doi: 10.1007/s10479-005-5723-0
Review of Kernel Methods for Pattern Analysis
Kroese, D. P. (2005). Review of Kernel Methods for Pattern Analysis. Siam Review, 47 (2), 385-387. doi: 10.1137/SIREAD000047000002000367000001
The cross-entropy method for network reliability estimation
Hui, K. P., Bean, N., Kraetzl, M. and Kroese, D. P. (2005). The cross-entropy method for network reliability estimation. Annals of Operations Research, 134 (1), 101-118. doi: 10.1007/s10479-005-5726-x
Erratum: A generalised Markov sampler (Methodology and Computing in Applied Probability 6:1 (29-53))
Keith, , Kroese, and Bryant, (2004). Erratum: A generalised Markov sampler (Methodology and Computing in Applied Probability 6:1 (29-53)). Methodology and Computing in Applied Probability, 6 (3) doi: 10.1023/B:MCAP.0000026605.65154.56
A fast cross-entropy method for estimating buffer overflows in queuing networks
De Boer, P. T., Kroese, D. P. and Rubinstein, R. Y. (2004). A fast cross-entropy method for estimating buffer overflows in queuing networks. Management Science, 50 (7), 883-895. doi: 10.1287/mnsc.1030.0139
Keith, Jonathan M., Kroese, Dirk P. and Bryant, Darryn (2004). A generalized Markov sampler. Methodology And Computing In Applied Probability, 6 (1), 29-53. doi: 10.1023/B:MCAP.0000012414.14405.15
Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process
Kroese, D. P., Scheinhardt, W. R. W. and Taylor, P. J. (2004). Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process. Annals of Applied Probability, 14 (4), 2057-2089. doi: 10.1214/105051604000000477
The tree cut and merge algorithm for estimation of network reliability
Hui, KP, Bean, N, Kraetzl, M and Kroese, D (2003). The tree cut and merge algorithm for estimation of network reliability. Probability In The Engineering And Informational Sciences, 17 (1), 23-45. doi: 10.1017/S0269964803171021
On the importance function in splitting simulation
Garvels, Marnix J. J., van Ommeren, Jan- Kees C. W. and Kroese, Dirk P. (2002). On the importance function in splitting simulation. European Transactions on Telecommunications, 13 (4), 363-371. doi: 10.1002/ett.4460130408
A simulated annealing algorithm for finding consensus sequences
Keith, Jonathan M., Adams, Peter, Bryant, Darryn, Kroese, Dirk P., Mitchelson, Keith R., Cochran, Duncan A. E. and Lala, Gita H. (2002). A simulated annealing algorithm for finding consensus sequences. Bioinformatics, 18 (11), 1494-1499. doi: 10.1093/bioinformatics/18.11.1494
Efficient simulation of a Tandem Jackson Network
Kroese, D. P. and Nicola, V. F. (2002). Efficient simulation of a Tandem Jackson Network. ACM Transactions on Modeling and Computer Simulation, 12 (2), 119-141. doi: 10.1145/566392.566395
Joint distributions for interacting fluid queues
Kroese, D. P. and Scheinhardt, W. R. W. (2001). Joint distributions for interacting fluid queues. Queueing Systems, 37 (1-3), 99-139. doi: 10.1023/A:1011044217695
On the decay rates of buffers in continuous flow lines
Kroese, D. P. (2000). On the decay rates of buffers in continuous flow lines. Methodology and Computing in Applied Probability, 2 (4), 425-441. doi: 10.1023/A:1010066319278
Efficient estimation of overflow probabilities in queues with breakdowns
Kroese, Dirk P. and Nicola, Victor F. (1999). Efficient estimation of overflow probabilities in queues with breakdowns. Performance Evaluation, 36-37, 471-484. doi: 10.1016/S0166-5316(99)00036-X
Efficient Simulation of Backlogs in Fluid Flow Lines
Kroese, Dirk P. and Nicola, Victor F. (1998). Efficient Simulation of Backlogs in Fluid Flow Lines. AEU-Archiv fur Elektronik und Ubertragungstechnik, 52 (3), 165-171.
Heavy traffic analysis for continuous polling models
Kroese, DP (1997). Heavy traffic analysis for continuous polling models. Journal of Applied Probability, 34 (3), 720-732. doi: 10.2307/3215097
Light-traffic analysis for queues with spatially distributed arrivals
Kroese, DP and Schmidt, V (1996). Light-traffic analysis for queues with spatially distributed arrivals. Mathematics of Operations Research, 21 (1), 135-157. doi: 10.1287/moor.21.1.135
Single-Server Queues with Spatially Distributed Arrivals
Kroese, DP and Schmidt, V (1994). Single-Server Queues with Spatially Distributed Arrivals. Queueing Systems, 17 (1-2), 317-345. doi: 10.1007/BF01158698
Kroese, Dirk and Schmidt, Volker (1993). Queueing systems on a circle. Zeitschrift fuer Operations Research, 37 (3), 303-331. doi: 10.1007/BF01415999
A continuous polling system with general service times
Kroese, Dirk P. and Schmidt, Volker (1992). A continuous polling system with general service times. Annals of Applied Probability, 2 (4), 906-927.
Second-order asymptotics in level crossing for differences of renewal processes
Kroese, D. P. and Kallenberg, W. C.M. (1992). Second-order asymptotics in level crossing for differences of renewal processes. Stochastic Processes and their Applications, 40 (2), 309-323. doi: 10.1016/0304-4149(92)90016-J
The difference of two renewal processes: level crossing and the infimum
Kroese, D. P. (1992). The difference of two renewal processes: level crossing and the infimum. Stochastic Models, 8 (2), 221-243. doi: 10.1080/15326349208807222
Approximations to the Lifetime Distribution of K-Out-of-N Systems with Cold Standby
Kroese, DP and Kallenberg, Wcm (1989). Approximations to the Lifetime Distribution of K-Out-of-N Systems with Cold Standby. Mathematics of Operations Research, 14 (3), 485-501. doi: 10.1287/moor.14.3.485
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
Inventory control with partially observable states
Wang, Erli, Kurniawati, Hanna and Kroese, Dirk P. (2019). Inventory control with partially observable states. 23rd International Congress on Modelling and Simulation - Supporting Evidence-Based Decision Making: The Role of Modelling and Simulation, MODSIM 2019, Canberra, ACT, Australia, 1 - 6 December 2019. Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). doi: 10.36334/modsim.2019.B1.wang
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
An on-line planner for POMDPs with large discrete action space: A quantile-based approach
Wang, Erli, Kurniawati, Hanna and Kroese, Dirk P. (2018). An on-line planner for POMDPs with large discrete action space: A quantile-based approach. 28th International Conference on Automated Planning and Scheduling ICAPS 2018, Delft, Netherlands, 24 - 29 June 2018. Menlo Park, CA United States: AAAI Press.
On a generalized splitting method for sampling from a conditional distribution
L'Ecuyer, Pierre, Botev, Zdravko I. and Kroese, Dirk P. (2018). On a generalized splitting method for sampling from a conditional distribution. 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.2018.8632422
CEMAB: a cross-entropy-based method for large-scale multi-armed bandits
Wang, Erli, Kurniawati, Hanna and Kroese, Dirk P. (2017). CEMAB: a cross-entropy-based method for large-scale multi-armed bandits. ACALCI 2017 Australasian Conference on Artificial Life and Computational Intelligence, Geelong, VIC, Australia, 31 January – 2 February 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-51691-2_30
Efficient estimation of tail probabilities of the typical distance in preferential attachment models
Grant, Morgan R. and Kroese, Dirk P. (2017). Efficient estimation of tail probabilities of the typical distance in preferential attachment models. 2016 Winter Simulation Conference, WSC 2016, Arlington, VA, United States, 11 - 14 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2016.7822101
Estimating the number of vertices in convex polytopes
Salomone, Robert, Vaisman, Radislav and Kroese, Dirk (2016). Estimating the number of vertices in convex polytopes. 4th Annual International Conference on Operations Research and Statistics (ORS 2016), 5th Annual Conference on Computational Mathematics, Computational Geometry & Statistics (CMCGS 2016), Singapore, Singapore, 18 - 19 January 2016. Singapore, Singapore: Global Science and Technology Forum. doi: 10.5176/2251-1938_ORS16.25
Rare event probability estimation for connectivity of large random graphs
Shah, Rohan, Hirsch, Christian, Kroese, Dirk P. and Schmidt, Volker (2015). Rare event probability estimation for connectivity of large random graphs. Winter Simulation Conference, WSC 2014, Savannah, GA, United States, 7-10 December 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2014.7019916
Efficient simulation of charge transport in deep-trap media
Brereton, Tim J., Kroese, Dirk P., Stenzel, Ole, Schmidt, Volker and Baumeier, Bjorn (2012). Efficient simulation of charge transport in deep-trap media. Winter Simulation Conference, Berlin, Germany, 9-12 December 2012. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2012.6465003
Fitting mixture importance sampling distributions via improved cross-entropy
Brereton, Tim J., Chan, Joshua C. C. and Kroese, Dirk P. (2011). Fitting mixture importance sampling distributions via improved cross-entropy. 2011 Winter Simulation Conference, Phoenix, AZ, United States, 11-14 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/WSC.2011.6147769
Stacey, Karl W. and Kroese, Dirk P. (2011). Greedy servers on a torus. 2011 Winter Simulation Conference, Phoenix, AZ, United States, 11-14 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/WSC.2011.6147764
Optimal generation expansion planning via the cross-entropy method
Kothari, Rishabh P. and Kroese, Dirk P. (2009). Optimal generation expansion planning via the cross-entropy method. 2009 Winter Simulation Conference (ERA Rank B), Austin, Texas, 13-16 December 2009. United States: IEEE - Inst Electrical Electronics Engineers Inc. doi: 10.1109/WSC.2009.5429296
Randomized methods for solving the Winner Determination Problem in combinatorial auctions
Chan, J. C. C. and Kroese, D. P. (2008). Randomized methods for solving the Winner Determination Problem in combinatorial auctions. Winter Simulation Conference 2008 (WSC 2008), Miami, United States, 7-10 December, 2008. Piscataway, NJ, U.S.A.: IEEE. doi: 10.1109/WSC.2008.4736208
The Generalized Gibbs Sampler and the Neighborhood Sampler
Keith, J. M., Sofronov, G. Y. and Kroese, D. P. (2008). The Generalized Gibbs Sampler and the Neighborhood Sampler. 7th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, Ulm, Germany, 14-18 August, 2006. Berlin: Springer-Verlag. doi: 10.1007/978-3-540-74496-2_31
Identifying change-points in biological sequences via sequential importance sampling
Sofronov, G. Y., Evans, G. E., Keith, J. M. and Kroese, D. P. (2007). Identifying change-points in biological sequences via sequential importance sampling. 17th Biennial Congress on Modelling and Simulation (MODSIM07), Christchurch, New Zealand, 10-13 December, 2007. Christchurch, New Zealand: Modelling and Simulation Society of Australia and New Zealand.
Optimal epidemic intervention of HIV spread using the cross-entropy method
Sani, A. and Kroese, D. P. (2007). Optimal epidemic intervention of HIV spread using the cross-entropy method. 17th Biennial Congress on Modelling and Simulation (MODSIM07), Christchurch, New Zealand, 10-13 December, 2007. Christchurch, New Zealand: Modelling and Simulation Society of Australia and New Zealand.
Parallel cross-entropy optimization
Evans, G. E., Keith, J. M. and Kroese, D. P. (2007). Parallel cross-entropy optimization. 2007 Winter Simulation Conference, Washington, 9-12 December, 2007. Washington: IEEE. doi: 10.1145/1360000/1351930/p2196-evans.pdf?key1=1351930
Generalized cross-entropy methods for rare events and optimization
Botev, Z. I., Kroese, D. P. and Taimre, T. (2006). Generalized cross-entropy methods for rare events and optimization. 6th International Workshop on Rare Event Simulation (RESIM 2006), Bamberg, Germany, 8-10 October, 2006.
Designing an optimal network using the cross-entropy method
Nariai, Sho, Hui, Kin-Ping and Kroese, Dirk P. (2005). Designing an optimal network using the cross-entropy method. Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005), Brisbane, Australia, 6-8 July 2005. Heidelberg, Germany: Springer. doi: 10.1007/11508069_30
On the Design of Multi-type Networks via the Cross-Entropy Method
Nariai, S. and Kroese, D. P. (2005). On the Design of Multi-type Networks via the Cross-Entropy Method. DRCN 2005, Naples, Italy, 16-19 October 2005. Italy: IEEE. doi: 10.1109/DRCN.2005.1563852
Global likelihood optimization via the cross-entropy method with an application to mixture models
Botev, Zdravko and Kroese, Dirk P. (2004). Global likelihood optimization via the cross-entropy method with an application to mixture models.
Global Likelihood Optimization Via The Cross-Entropy Method With An Application To Mixture Models
Botev, Z. I. and Kroese, D. P. (2004). Global Likelihood Optimization Via The Cross-Entropy Method With An Application To Mixture Models. 2004 Winter Simulation Conference, Washington, USA, 5-8 December, 2004. Washington: Board of Winter Simulation Conference.
The transform likelihood ratio method for rare event simulation with heavy tails
Kroese, D. P. and Rubinstein, R. Y. (2004). The transform likelihood ratio method for rare event simulation with heavy tails. United States: Springer New York LLC. doi: 10.1023/B:QUES.0000027989.97672.be
Network reliability estimation using the tree cut and merge algorithm with importance sampling
Hui, K.-P., Bean, N.G., Kraetzl, M. and Kroese, D. P. (2003). Network reliability estimation using the tree cut and merge algorithm with importance sampling. DRCN2003, Banff, Canada, 19-22 October 2003. Canada: The Institute of Electrical & Electronics Engineers, Inc. doi: 10.1109/DRCN.2003.1275364
Estimating buffer overflows in three stages using cross-entropy
de Boer, P.T., Kroese, D. P. and Rubinstein, R.Y. (2002). Estimating buffer overflows in three stages using cross-entropy. 35th Winter Simulation Conference (ERA Rank B), San Diego, USA, 3-11 December 2002. United States: IEEE - Computer Society. doi: 10.1109/WSC.2002.1172899
Sequence alignment by rare event simulation
Keith, Jonathan and Kroese, Dirk P. (2002). Sequence alignment by rare event simulation. 35th 2002 Winter Simulation Conference (ERA Rank B), San Diego, CA, U.S.A., 8-11 December 2002. United States: IEEE - Computer Society. doi: 10.1109/WSC.2002.1172901
Efficient simulation of a tandem Jackson network
Kroese, Dirk P. and Nicola, Victor F. (1999). Efficient simulation of a tandem Jackson network. 1999 Winter Simulation Conference Proceedings (WSC), , , December 5, 1999-December 8, 1999.
Comparison of RESTART implementations
Garvels, Marnix J J and Kroese, Dirk P. (1998). Comparison of RESTART implementations. Proceedings of the 1998 Winter Simulation Conference, WSC. Part 1 (of 2), , , December 13, 1998-December 16, 1998. IEEE.
A comparison of RESTART implementations
Garvels, M. J. J . and Kroese, D. P. (1998). A comparison of RESTART implementations. Winter Simulation Conference, Washington, DC, United States, 13-16 Dec 1998.
Efficient simulation of backlogs in fluid flow lines
Kroese, DP and Nicola, VF (1998). Efficient simulation of backlogs in fluid flow lines. Workshop on Rare Event Simulation, Aachen Germany, Aug 28-29, 1997. JENA: GUSTAV FISCHER VERLAG.
Annals of Operations Research. (2005). 134 (1)
Improved Cross-Entropy Method for Estimation
Joshua C. C. Chan and Dirk P. Kroese (2010). Improved Cross-Entropy Method for Estimation. School of Economics, University of Queensland.
Heavy Tails, Importance Sampling and Cross-Entropy
Asmussen, S., Kroese, D. P. and Rubinstein, R. Y. (2004). Heavy Tails, Importance Sampling and Cross-Entropy.
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries
(2020–2023) ARC Discovery Projects
High Quality and Robust Energy Conversion Systems for Distribution Networks
(2018–2021) ARC Linkage Projects
Large Scale Sequential Decision Making in an Uncertain World.
(2017–2019) Office of Naval Research, Dept of the Navy, USA
(2014–2021) University of Melbourne
Advanced Monte Carlo Methods for Spatial Processes
(2014–2016) ARC Discovery Projects
Monte Carlo Methods for Spatial Stochastic Modeling
(2012–2013) Go8 Australia - Germany Joint Research Co-operation Scheme
New-generation parallel-computing cluster for the mathematical and physical sciences
(2011) UQ Major Equipment and Infrastructure
Improved Monte Carlo Methods for Estimation, Optimisation, and Counting
(2009–2013) ARC Discovery Projects
Cross-Entropy Methods in Complex Biological Systems
(2005–2007) ARC Discovery Projects
Rare Event Simulation with Heavy Tails
(2005–2007) ARC Discovery Projects
Reinforcement Learning for Large and Complex Partially Observable Markov Decision Processes
Doctor Philosophy — Associate Advisor
Other advisors:
Active Front End Power Electronics converter: modeling, control and analysis
Doctor Philosophy — Associate Advisor
Other advisors:
Optimization Methods for Generalized Convex Problems
Doctor Philosophy — Associate Advisor
Other advisors:
Impacts of Grid Connected Inverters on Distribution Transformer
Doctor Philosophy — Associate Advisor
Other advisors:
Decision Making In An Uncertain World
(2019) Doctor Philosophy — Principal Advisor
Sequential Monte Carlo for Random Graphs
(2019) Master Philosophy — Principal Advisor
Advances in Monte Carlo Methodology
(2018) Doctor Philosophy — Principal Advisor
Other advisors:
Optimization by Rare-event Simulation
(2018) Doctor Philosophy — Principal Advisor
Other advisors:
Monte Carlo Methods for Discrete Problems
(2017) Doctor Philosophy — Principal Advisor
Other advisors:
Markov Chain Monte Carlo for Rare-Event Probability Estimation
(2013) Doctor Philosophy — Principal Advisor
Other advisors:
Monte Carlo Methods for Complicated Stochastic Models
(2013) Doctor Philosophy — Principal Advisor
Advanced Monte Carlo methods with applications in finance
(2010) Doctor Philosophy — Principal Advisor
(2010) Doctor Philosophy — Principal Advisor
Other advisors:
Advances in Cross-Entropy Methods
(2009) Doctor Philosophy — Principal Advisor
Parallel and sequential Monte Carlo methods with applications
(2009) Doctor Philosophy — Principal Advisor
Stochastic Modelling and Intervention of the Spread of HIV/AIDS
(2009) Doctor Philosophy — Principal Advisor
Cross-Entropy Method in Telecommunication Systems
(2008) Doctor Philosophy — Principal Advisor
Other advisors:
Estimation of Distribution Algorithms for Single- and Multi-Objective Optimization
(2014) Doctor Philosophy — Associate Advisor
Other advisors:
Simulation of Stochastic Transport in Complex Systems Using Quantum Techniques
(2014) Master Philosophy — Associate Advisor
Other advisors:
Vehicle and Crew Routing and Scheduling
(2011) Doctor Philosophy — Associate Advisor
Other advisors:
TOPICS IN QUASISTATIONARITY FOR MARKOV CHAINS
(2008) Master Philosophy — Associate Advisor
TRIGONOMETRIC SCORES RANK PROCEDURES WITH APPLICATIONS TO LONG-TAILED DISTRIBUTIONS
(2006) Doctor Philosophy — Associate Advisor