Publications of Dirk P. Kroese

• Chan, J.C.C. and Kroese, D.P. (2025). Statistical Modeling and Computation, Second Edition. Springer, New York. Springer Texts in Statistics.
• Hoerger, M., Kurniawati, H., Kroese, D.P., and Ye, N. (2024). Adaptive Discretization using Voronoi Trees for Continuous POMDPs. The International Journal of Robotics Research 43 (9), 1283-1298.
• Hoerger M., Kurniawati H., Kroese, D.P. and Ye, N. (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).
• Kroese, D.P. and Botev, Z.I. (2023). An Advanced Course in Probability and Stochastic Processes. CRC Press, Boca Raton.
• Ju, J., Kurniawati, H., Kroese, D.P., and Ye, N. (2023). Model-based offline reinforcement learning for sustainable fishery management. Expert Systems. DOI: 10.1111/exsy.13324. (pdf)
• Hoerger, M., Kurniawati, H., Kroese, D.P., and Ye, N. (2023). A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees. arXiv:2305.08049. (pdf)
• Gibson, L., Hoerger, M., and Kroese, D.P. (2023). A Flow-Based Generative Model for Rare-Event Simulation. arXiv:2305.07863. (pdf)
• Hoerger, M., Kurniawati, H., Kroese D.P., and Ye, N. (2023). Adaptive Discretization using Voronoi Trees for Continuous POMDPs. arXiv:2302.10439. To appear in The International Journal of Robotics Research. (pdf)
• Ju, J., Kurniawati, H., Kroese, D.P., and Ye, N. (2022). MOOR: Model-based Offline Reinforcement Learning for Sustainable Fishery Management. Proc. Int. International Congress on Modelling and Simulation (MODSIM). (pdf)
• Van der Heide, C., Hodgkinson, L., Roosta, F., and Kroese, D.P. Shadow Manifold Hamiltonian Monte Carlo. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021, San Diego, California, USA. PMLR: Volume 130. (pdf)
• Hirsch, C., Moka, S.B., Taimre, T., Kroese, D.P. (2021). Rare Events in Random Geometric Graphs. Methodol. Comput. Appl. Probab. DOI:10.1007/s11009-021-09857-7. (pdf)
• Shukla, A., Nguyen, T., Moka, S.B., Ellis, J., Grady, J., Oey, H., Cristino, A., Khanna, K.K., Kroese, D.P., Krause, L., Dray, E., Fink, J.L., and Duijf, P. (2020), Chromosome arm aneuploidies shape tumour evolution, cancer prognosis and drug response. Nature Communications 11, Article Number 449. DOI: 10.1038/s41467-020-14286-0. (link)
• Moka, S.B. and Kroese, D.P. (2020). Perfect Sampling for Gibbs Point Processes Using Partial Rejection Sampling. Bernoulli 26 (3), 2082-2104. (pdf). DOI: 10.3150/19-BEJ1184
• Hirsch, C., Moka, S.B., Taimre, T., Kroese, D.P. (2020), Rare Events in Random Geometric Graphs. arXiv:2007.05965 (pdf)
• Kroese, D.P., Botev, Z.I, Taimre, T. and Vaisman, R. (2019). Data Science and Machine Learning: Mathematical and Statistical Methods. Chapman and Hall/CRC, Boca Raton.
• Wang E., Kurniawati, H. and Kroese, D.P. (2019). Inventory control with partially observable states. In Elsawah, S. (ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2019, pp. 200--206. ISBN: 978-0-9758400-9-2. https://doi.org/10.36334/modsim.2019.B1.wang
• Moka, S.B., Kroese, D.P. and Juneja, S. (2019). Unbiased estimation of the reciprocal mean for non-negative random variables. Proceedings of the 2019 Winter Simulation Conference. N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. (pdf)
• Moka, S.B. and Kroese, D.P. (2019). Perfect Sampling for Gibbs Point Processes Using Partial Rejection Sampling. arXiv:1901.05624 (pdf)
• Taimre, T., Kroese, D.P, and Botev, Z.I. (2019). Monte Carlo Methods. Wiley StatsRef: Statistical Reference Online (pdf). DOI: 10.1002/9781118445112.stat03619.pub2
• Salomone, R., South, L.F., Drovandi, C.C., and Kroese, D.P. (2018). Unbiased and Consistent Nested Sampling via Sequential Monte Carlo. arXiv:2266894 (pdf).
• Wang, E., Kurniawati, H., and Kroese, D.P. (2018). An On-line Planner for POMDPs with Large Discrete Action Space: A Quantile-Based Approach. Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS'2018) . (pdf).
• Botev, Z.I., Chen, Y.-L., L'Ecuyer, P., MacNamara, S., and Kroese, D.P. (2018). Exact Posterior Simulation from the Linear Lasso Regression Proceedings of the 2018 Winter Simulation Conference, M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, and B. Johansson, eds. (pdf).
• L'Ecuyer, P., Botev, Z.I. and Kroese, D.P. (2018). On A Generalized Splitting Method For Sampling From A Conditional Distribution. Proceedings of the 2018 Winter Simulation Conference, M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, and B. Johansson, eds. (pdf).
• Vaisman, R. and Kroese, D.P. (2017). On the analysis of independent sets via multilevel splitting. Networks 71 (3), 281--301. (pdf). DOI: 10.1002/net.21805
• Duan, Q. and Kroese, D.P. (2018). Splitting for multi-objective optimization. Methodology and Computing in Applied Probability 20 (2), 517--533. (pdf). DOI: 10.1007/s11009-017-9572-5
• Shah, R. and Kroese, D.P. (2017). Without replacement sampling for particle methods on finite state spaces. Statistics and Computing 28 (3), 633--652. (pdf). doi:10.1007/s11222-017-9752-8
• Vaisman, R, Roughan, M, and Kroese, D.P. (2017). The multilevel splitting algorithm for graph coloring with application to the Potts model. Philosophical Magazine 97 (19), 1646--1673. (pdf). doi:10.1080/14786435.2017.1312023
• Vaisman, R. and Kroese, D.P. (2017). Stochastic Enumeration Method for Counting Trees. Methodology and Computing in Applied Probability 19, 31--73. doi:10.1007/s11009-015-9457-4 (pdf).
• Benham, T., Duan, Q., Kroese, D.P. and Liquet, B. (2017). CEoptim: Cross-Entropy R Package for Optimization. Journal of Statistical Software 76 (8) (pdf). (CRAN) doi:10.18637/jss.v076.i08
• Rubinstein, R. Y. , Kroese, D. P. (2017). Simulation and the Monte Carlo Method, 3rd edition, John Wiley & Sons.
• Wang, E., Kurniawati H., Kroese, D.P. (2017). CEMAB: A Cross-Entropy-based method for large-scale multi-armed bandits. In: Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017). X. Li, T. Hendtlass, M. Wagner, eds., pp. 353-365, 2017. DOI: 10.1007/978-3-319-51691_230. (pdf).
• Vaisman, R., Kroese, D.P., and Gertsbakh, I. (2016). Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks. Structural Safety. DOI: 10.1016/j.strusafe.2016.07.001. (pdf).
• Grant, M.R. and Kroese, D.P. Efficient estimation of tail probabilities of the typical distance in preferential attachment models.(2016) Proceedings of the 2016 Winter Simulation Conference, T.M.K. Roeder, P.I. Frazier, R. Szechtman, and E. Zhou, eds., pp. 338-346. (pdf).
• Scheinhardt, W.R.W. and Kroese, D.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. (pdf).
• Duan, Q. and Kroese, D.P. (2016). Splitting for Optimization. Computers and Operations Research 73, 119--131. DOI:10.1016/j.cor.2016.04.015. (pdf).
• Salomone, R., Vaisman, R., and Kroese, D.P. (2016). Estimating the Number of Vertices in Convex Polytopes. Proceedings of the Annual International Conference on Operations Research and Statistics, ORS 2016 . (pdf).
• Vaisman, R., Kroese, D.P., and Gertsbakh, I.B. (2016). Improved Sampling Plans for Combinatorial Invariants of Coherent Systems. IEEE Trans. Rel. 65 (1), 410-424, DOI: 10.1109/TR.2015.2446471 (pdf).
• Spettl, A., Brereton, T., Duan, Q. Werz,T., Krill III, C.E., Kroese, D.P., and Schmidt, V. (2016). Fitting Laguerre tessellation approximations to tomographic image data. Philosophical Magazine 96 (2), 166-189. (pdf). doi:10.1080/14786435.2015.1125540
• Shah,R. and Kroese, D.P. (2015). Estimating residual connectivity for random graphs. arXiv:1506.01117. (pdf).
• 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. Modeling Simulation Mater. Sci. Eng. 23 (4). DOI:10.1088/0965-0393/23/4/045003 (pdf).
• Kroese, D.P. and Chan, J.C.C. (2014). Statistical Modeling and Computation. Springer, New York.
• Brereton, T., Hirsch, C., Schmidt, V., and Kroese, D.P. (2014). A critical exponent for shortest-path scaling in continuum percolation. Journal of Physics A 47 505003. DOI:10.1088/1751-8113/47/50/505003 (pdf).
• Shah R., Hirsch C., Kroese D.P., and Schmidt, V. (2014). Rare event probability estimation for connectivity of large random graphs. Proceedings of the 2014 Winter Simulation Conference, A Tolks, S.D. Diallo, I.O, Ryzhov, L. Yilmaz, S. Buckley, and J.A. Miller, eds., pp 510-521 (pdf).
• Kroese D.P., Brereton T., Taimre T., and Botev, Z.I. (2014). Why the Monte Carlo Method is so important today. Wiley Interdisciplinary Reviews: Computational Statistics 6, 386-392. DOI: 10.1002/wics.1314 (pdf).
• Duan Q., Kroese D.P., Brereton T., Spettl A., and Schmidt V. (2014). Inverting Laguerre Tessellations. The Computer Journal 9, 1431-1440. DOI: 10.1093/comjnl/bxu029 (pdf).
• Stenzel, O., Hirsch, C., Brereton T., Baumeier, B., Andrienko, D., Kroese, D.P., and Schmidt, V. (2014). A general framework for consistent estimation of charge transport properties via random walks in random environments. Multiscale Model. Simul. 12 (3), 1108-1134 (pdf).
• Grace A.W., Kroese D.P., and Sandmann W. (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 (pdf).
• Scheinhardt, W.R.W. and Kroese, D.P. (2014). Computing the drift of random walks in dependent random environments. arXiv:1406.3390 (pdf).
• Kroese, D.P. and Botev, Z.I. (2014). Spatial Process Generation. In: V. Schmidt (Ed.). Lectures on Stochastic Geometry, Spatial Statistics and Random Fields, Volume II: Analysis, Modeling and Simulation of Complex Structures, Springer-Verlag, Berlin. arXiv: 1308.0399 (pdf).
• Brereton, T., Chan J.C.C., and Kroese, D.P. (2013). Monte Carlo Methods for Portfolio Credit Risk. In: Credit Portfolio Securitizations and Derivatives, H. Scheule and D. Rosch (Eds.), John Wiley & Sons, New York, pp 128 - 151. (pdf)
• Brereton, T., Stenzel, O., Baumeier B., Andienko, D., Schmidt, V., Kroese D. P. (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 (pdf)
• 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 Simulation Mater. Sci. Eng. 21 (5). DOI: 10.1088/0965-0393/21/5/055004. (pdf)
• Kroese, D.P., Rubinstein, R.Y, and Glynn, P.W. (2013). The Cross-Entropy Method for Estimation. In Handbook of Statistics, Volume 31: Machine Learning: Theory and Applications, V. Govindaraju and C.R. Rao, Eds, Chennai: Elsevier B.V., pp. 19-34. (pdf)
• Botev, Z.I., Kroese, D.P., Rubinstein, R.Y, and L'Ecuyer, P. (2013). The Cross-Entropy Method for Optimization. In Handbook of Statistics, Volume 31: Machine Learning: Theory and Applications, V. Govindaraju and C.R. Rao, Eds, Chennai: Elsevier B.V., pp. 35-59. (pdf) doi:10.1016/b978-0-444-53859-8.00003-5
• Brereton, T., Kroese, D.P., Stenzel, O., Schmidt, Baumeier, B. (2012). Efficient simulation of charge transport in deep-trap media, Proceedings of the 2012 Winter Simulation Conference, C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher, eds. (pdf)
• Kroese, D.P., Rubinstein, R.Y. (2012). Monte Carlo Methods. Wiley Interdisciplinary Reviews: Computational Statistics 4 , 48-58. DOI: 10.1002/wics.194 . (pdf)
• Chan, J.C.C. and Kroese, D.P. (2012). Improved cross-entropy method for estimation. Statistics and Computing 22 (5) 1031-1040. (pdf)
• Brereton, T.I, Chan, J.C.C, and Kroese, D.P. (2011). Fitting mixture importance sampling distributions via improved cross-entropy. Proceedings of the 2011 Winter Simulation Conference. S. Jain, R. R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds., pp. 422-428. (pdf)
• Stacey, K. W. and Kroese, D.P. (2011) Greedy servers on a torus. Proceedings of the 2011 Winter Simulation Conference. S. Jain, R. R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds., pp. 369-380. (pdf)
• 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., Rubinstein R. Y., Cohen I., Porotsky S. and T. Taimre "Cross-Entropy Method", in Encyclopedia of Operations Research and Management Sciences, third edition (S. I. Gass and M. C. Fu, Eds.), Springer-Verlag, 2011. (pdf)
• Chan, J.C.C, Glynn P.W., and Kroese, D.P. (2011). A comparison of cross-entropy and variance minimization strategies. Journal of Applied Probability 48A, 183-194. (pdf)
• Botev, Z.I. and Kroese, D.P. (2012). Efficient Monte Carlo simulation via the Generalized Splitting Method. Statistics and Computing. 22 (1), 1-16. (pdf)
• Botev, Z.I., Kroese, D.P. (2011). The Generalized Cross Entropy Method, with Applications to Probability Density Estimation. Methodology and Computing in Applied Probability . 13 (1), 1-27. (pdf)
• Kroese, D.P. (2011). The Cross-Entropy Method. In Wiley Encyclopedia of Operations Research and Management Science J. Cochran, L. A. Cox, Jr., P. Keskinocak, J. P. Kharoufeh, J. C. Smith (Eds.) John Wiley and Sons, New York. (pdf)
• Rojas-Nandayapa, L, Foss, S., and Kroese, D.P. Stability and Performance of Greedy Server Systems: A Review and Open Problems. (2011) Queueing Systems: Theory and Applications 68, 221-227. (pdf)
• Botev, Z.I., Grotowski, J.F, and Kroese, D. P. (2010). Kernel density estimation via diffusion. Annals of Statistics 38 (5), 2916-2957 (pdf) . For the matlab code please visit matlabcentral.
• Evans G. E., Sofronov G. Yu., Keith J. M., and Kroese D. P. (2010). Estimating Change-Points in Biological Sequences via the Cross-Entropy Method. Annals of Operations Research. 189 (1), 155-165. (pdf)
• Chan, J.C.C. and Kroese, D.P. (2010). Efficient Estimation of Large Portfolio Loss Probabilities in t-copula Models European Journal of Operational Research, 205 (2), 361-367. (pdf)
• Chan, C. C., Kroese, D.P. (2010). Rare-event Probability Estimation with Conditional Monte Carlo. Annals of Operations Research 189 (1), 43-61. (pdf)
• Kothari, R. P. and Kroese, D.P. (2009). Optimal generation expansion planning via the cross-entropy method. Proceedings of the 2009 Winter Simulation Conference. M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin, and R. G. Ingalls, eds. pp. 1482-1491 (pdf)
• Sofronov G. Yu., Evans G. E., Keith J. M., Kroese D. P. (2009). Identifying Change-points in Biological Sequences via Sequential Importance Sampling. Environmental Modeling & Assessment 14 (5), 577-584. (pdf)
• Belay A., O'Brien, E.G, and Kroese, D.P. (2008). Truck Flee t Model for Design and Assessment of Flexible Pavements. Journal of Sound and Vibration 311 (3-5) 1161-1174. (pdf)
• Sani, A, Kroese, D.P. (2008). Controling the number of HIV infectives in a mobile population. Mathematical Biosciences 213 103-112. (pdf)
• Botev, Z.I., 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. (pdf)
• Chan, C.C., Kroese, D.P. (2008). Randomized methods for solving the Winner Determination Problem in combinatorial auctions. Proceedings of the 2008 Winter Simulation Conference, S. J. Mason, R. R. Hill, L. Moench, O. Rose, T. Jefferson, J. W. Fowler eds., pp. 1344-1349. (pdf)
• Botev, Z.I., Kroese, D.P. (2008). Non-asymptotic bandwidth selection for density estimation of discrete data. Methodology and Computing in Applied Probability 10 435-451. (ps)
• Keith, J.M., Kroese, D.P. and Sofronov, G. Yu. (2008) Adaptive Independence Samplers. Statistics and Computing. 18 (4) 409-420. (pdf)
• Botev, Z.I, Kroese, D.P., Taimre, T. (2007). Generalized Cross-Entropy Methods with Applications to Rare-Event simulation and Optimization. Simulation 83 (11) 785 - 806. (pdf)
• Costa, A., Jones, O.D, Kroese, D. P. (2007). Convergence Properties of the Cross-Entropy Method for Discrete Optimization. Operations Research Letters 35 (5), 573-580. (pdf)
• Sani, A. and Kroese, D.P. (2007) Optimal Epidemic Intervention of HIV Spread Using the Cross-Entropy Method. In Kulasiri, D. and Oxley, L. (Eds.) Proceedings of the International Congress on Modelling and Simulation (MODSIM), Modelling and Simulation Society of Australia and New Zealand, pp. 448-454. (pdf)
• Evans, G. , Keith, J.M, Kroese, D.P (2007). Parallel Cross-Entropy Optimization. Proceedings of the 2007 Winter Simulation Conference , Washington DC, pp. 2196-2202. (pdf)
• Rubinstein, R. Y. , Kroese, D. P. (2007). Simulation and the Monte Carlo Method, 2nd edition, John Wiley & Sons.
• Rubinstein, R.Y, Kroese, D.P, Dolgin, A. and Glynn, P. W. (2007). Parametric Minimum Cross-Entropy Method for Counting the Number of Satisfiability Assignments. (abstract)
• Keith, J.M., Sofronov, G. Yu. and Kroese, D.P. (2007) The Generalized Gibbs Sampler and the Neighborhood Sampler. Proceedings of the 7-th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC 2006) (pdf)
• Kroese, D.P., Nariai, S, Hui, K-P (2007). Network Reliability Optimization via the Cross-Entropy Method. IEEE Trans. Rel. , 56 (2), 275-287. (pdf)
• Sani, A, Kroese, D.P, Pollett, P. (2007). Stochastic Models for the Spread of HIV in a Mobile Heterosexual Population. Mathematical Biosciences 208, 98-124. (pdf)
• Roberts, B., Kroese, D.P. (2007). Estimating the number of s-t paths in a graph. Journal of Graph Algorithms and Applications 11 (1), 195-214. (pdf)
• Kroese, D.P, Rubinstein, R.Y., Taimre, T. (2007). Application of the Cross-Entropy Method to Clustering and Vector Quantization. Journal of Global Optimization 37, 137-157. (pdf)
• Kroese, D.P., Hui, K.-P. (2007). Applications of the Cross-Entropy Method in Reliability. In Computational Intelligence in Reliability Engineering G. Levitin, ed., Springer-Verlag, 37 - 82. (pdf)
• Botev, Z.I, Kroese, D.P., Taimre, T. (2006). Generalized Cross-Entropy Methods. Proceedings of RESIM06, 1-30. (pdf)
• Sofronov, G, Keith, J.M., Kroese, D.P. (2006). An Optimal Sequential Procedure for a Buying-Selling Problem with Independent Observations. J. Appl. Prob. 43, 454-462 (pdf)
• Asmussen, S., Kroese, D.P. (2006). Improved algorithms for rare event simulation with heavy tails. Advances in Applied Probability 38 (2), 545-558. (pdf)
• Kroese, D.P, Porotsky, S., Rubinstein, R.Y. (2006). The Cross-Entropy Method for Continuous Multi-extremal Optimization. Methodology and Computing in Applied Probability 8, 383-407. (pdf)
• De Boer, P-T., Kroese, D.P, Mannor, S. and Rubinstein, R.Y. (2005). A Tutorial on the Cross-Entropy Method. Annals of Operations Research, 134 (1), 19-67. (pdf) doi:10.1007/s10479-005-5724-z
• Nariai S., Kroese, D.P., Hui, K.P. (2005). Designing an Optimal Network Using the Cross-Entropy Method. In: Lecture Notes in Computer Science: Intelligent Data Engineering and Automated Learning, Gallagher M., Hogan J., Maire F., Eds., Springer-Verlag. Winner of best student paper at IDEAL 2005: 6th International Conference, July 6-8, 2005. pp 228-233 (pdf)
• Nariai S., Kroese, D.P. (2005). On the Design of Multi-type Networks via the Cross-Entropy Method. Proceeding of the Fifth International Workshop on the Design of Reliable Communication Networks (DRCN 2005), pp. 109- 114 (pdf).
• Asmussen, S., Kroese, D.P., Rubinstein, R.Y. (2005). Heavy Tails, Importance Sampling and Cross-Entropy. Stochastic Models 21 (1), 57-76. (pdf)
• Rubinstein, R.Y., Kroese, D.P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning, Springer-Verlag, New York.
• Botev, Z., Kroese, D.P. (2004). Global Likelihood Optimization via the Cross-Entropy Method, with an Application to Mixture Models. Proceedings of the Winter Simulation Conference, Washington DC, pp 529-535. (pdf)
• Keith, J., Kroese, D.P., Bryant, D. (2004). A Generalized Markov Chain Sampler. Methodology and Computing in Applied Probability, 6 (1) 29-53. (pdf)
• 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. (pdf) http://dx.doi.org/10.1109/tr.2007.895303
• Kroese, D.P. (2005). Review of Kernel Methods for pattern Analysis, SIAM Review, 47 (2), 385-387.
• 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. (pdf) doi:10.1007/s10479-005-5728-8
• De Boer, P.-T., Kroese, D.P., Rubinstein, R.Y. (2004). A Fast Cross-Entropy Method for Estimating Buffer Overflows in Queueing Networks. Management Science, 50 (7), pp 883-895. (pdf)
• Kroese, D.P. and Rubinstein, R.Y. (2004). The Transform Likelihood Ratio Method for Rare Event Simulation with Heavy Tails. Queueing Systems, 46, pp 317-351. (pdf)
• Kroese, D.P., Scheinhardt, W.C.W. and Taylor, P.G. (2004). Spectral Properties of the Tandem Jackson Network, Seen as a Quasi-Birth-and-Death Process. Annals of Applied Probability 14 (4), pp 2057-2089. (pdf)
• Hui, K-P., Bean, N., Kraetzl, M. and Kroese, D.P. (2003). The Tree Cut and Merge Algorithm for Estimation of Network Reliability. Probability in the Engineering and Informational Sciences 17 23-45. (pdf)
• Hui, K-P., Bean, N, Kraetzl, M and Kroese, D.P. (2003). Network Reliability Estimation Using the Tree Cut and Merge Algorithm with Importance Sampling. Proceeding of the Fourth International Workshop on the Design of Reliable Communication Networks (DRCN 2003), pp. 254 - 262. (pdf)
• Keith J.M., , Adams P. , Bryant D., Kroese D.P., Mitchelson K.R., Cochran D.A.E. and Lala G.H. (2002). A Simulated Annealing Algorithm for Finding Consensus Sequences. Bioinformatics 18 1494-1499. (pdf)
• Garvels, M.J.J., Kroese, D.P., Van Ommeren J-K.C.W. (2002). On the importance function in splitting simulation. European Transactions on Telecommunications 13 (4) 363-371 (pdf)
• Kroese, D.P., Nicola V.F. (2002). Efficient Simulation of a Tandem Jackson Network. ACM Transactions on Modeling and Computer Simulation 12 (2), 199-141. (pdf)
• Keith, J., Kroese, D.P. (2002). Sequence Alignment By Rare Event Simulation. Proceedings of the 2002 Winter Simulation Conference , San Diego, 320 - 327. (pdf)
• De Boer, P.-T., Kroese, D.P., Rubinstein, R.Y. (2002). Estimating Buffer Overflows in Three Stages using Cross-Entropy Proceedings of the 2002 Winter Simulation Conference , San Diego, 301 - 309.
• Kroese, D.P., Scheinhardt, W.R.W. (2001). Joint distributions for interacting fluid queues. Queueing Systems, special issue on Stochastic Models with Tractable Steady State Characteristics, 37, 99-140. (pdf)
• Kroese, D.P. (2000). On the decay rates of buffers in continuous flow lines. Methodology and Computing in Applied Probability, 2, 425-441. (pdf)
• Kroese, D.P., Nicola V.F. (1999). Efficient estimation of overflow probabilities in queues with breakdowns. Performance Evaluation, 36-37 471-484. (pdf)
• Kroese, D.P., Nicola, V.F. (1998). Efficient simulation of backlogs in fluid flow lines, Int. J. Electron. Commun. (AEU) 52 (3), pp. 165-171. (pdf)
• Garvels, M.J.J., Kroese, D.P. (1998). A comparison of RESTART implementations. Proceedings of the Winter Simulation Conference , Washington, pp.601-609. (pdf)
• Kroese, D.P., Scheinhardt, W.R.W. (1998). A fluid queue driven by a fluid queue. In B. Goldstein, A. Koucheryavy and M. Shneps-Shneppe, editors, Teletraffic theory as a base for QoS: monitoring, evaluation, decisions, 389-400, St. Petersburg. (pdf)
• Kroese, D.P. (1997). Heavy-traffic analysis for continuous polling models, J. Appl. Probab. 34, pp. 720-732. (pdf)
• Kroese, D.P. , Schmidt, V. (1996). Light-traffic Analysis for Queues with Spatially Distributed Arrivals. Math. of O.R. 21 (1) 135-157. (pdf)
• Kroese, D.P. , Schmidt, V. (1994). Single-Server Queues with Spatially Distributed Arrivals. Queueing Systems 17 (I-II) 317-345. (pdf)
• Kroese, D.P. , Schmidt, V. (1993). Queueing Systems on a Circle. Zeitschrift f. Operations Res. 37 303-331. (pdf)
• Kroese, D.P. , Schmidt, V. (1992). A Continuous Polling System with General Service Times. Ann. Appl. Prob. 2 906-927. DOI: 10.1214/aoap/1177005580 (pdf)
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