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A Tutorial on the Cross-Entropy Method

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Cited by:

  1. Erik Hintz & Marius Hofert & Christiane Lemieux & Yoshihiro Taniguchi, 2022. "Single-Index Importance Sampling with Stratification," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 3049-3073, December.
  2. Daniel Berend & Shahar Golan & Yochai Twitto, 2022. "Using the method of conditional expectations to supply an improved starting point for CCLS," Journal of Combinatorial Optimization, Springer, vol. 44(5), pages 3711-3734, December.
  3. Enlu Zhou & Shalabh Bhatnagar, 2018. "Gradient-Based Adaptive Stochastic Search for Simulation Optimization Over Continuous Space," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 154-167, February.
  4. Chen, Siliang & Chen, Kang & Zhu, Xu & Jin, Xinqiao & Du, Zhimin, 2022. "Deep learning-based image recognition method for on-demand defrosting control to save energy in commercial energy systems," Applied Energy, Elsevier, vol. 324(C).
  5. Xu, Hai-Yan & Kuo, Shyh-Hao & Li, Guoqi & Legara, Erika Fille T. & Zhao, Daxuan & Monterola, Christopher P., 2016. "Generalized Cross Entropy Method for estimating joint distribution from incomplete information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 162-172.
  6. Junran Wu & Ke Xu & Xueyuan Chen & Shangzhe Li & Jichang Zhao, 2021. "Price graphs: Utilizing the structural information of financial time series for stock prediction," Papers 2106.02522, arXiv.org, revised Nov 2021.
  7. A. Shibu & M. Reddy, 2014. "Optimal Design of Water Distribution Networks Considering Fuzzy Randomness of Demands Using Cross Entropy Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4075-4094, September.
  8. M Caserta & E Quiñonez Rico, 2009. "A cross entropy-based metaheuristic algorithm for large-scale capacitated facility location problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1439-1448, October.
  9. Kailin Xie & Jianfei Yin & Hengyong Yu & Hong Fu & Ying Chu, 2024. "Passive Aggressive Ensemble for Online Portfolio Selection," Mathematics, MDPI, vol. 12(7), pages 1-19, March.
  10. Caserta, Marco & Reiners, Torsten, 2016. "A pool-based pattern generation algorithm for logical analysis of data with automatic fine-tuning," European Journal of Operational Research, Elsevier, vol. 248(2), pages 593-606.
  11. A. Gouda & T. Szántai, 2008. "Rare event probabilities in stochastic networks," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 16(4), pages 441-461, December.
  12. Heath, Jeffrey W. & Fu, Michael C. & Jank, Wolfgang, 2009. "New global optimization algorithms for model-based clustering," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3999-4017, October.
  13. Tito Homem-de-Mello, 2007. "A Study on the Cross-Entropy Method for Rare-Event Probability Estimation," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 381-394, August.
  14. Casas-Ramírez, Martha-Selene & Camacho-Vallejo, José-Fernando & Martínez-Salazar, Iris-Abril, 2018. "Approximating solutions to a bilevel capacitated facility location problem with customer's patronization toward a list of preferences," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 369-386.
  15. Altiparmak, Fulya & Dengiz, Berna, 2009. "A cross entropy approach to design of reliable networks," European Journal of Operational Research, Elsevier, vol. 199(2), pages 542-552, December.
  16. John Efromson & Roger Lawrie & Thomas Jedidiah Jenks Doman & Matthew Bertone & Aurélien Bègue & Mark Harfouche & Dominic Reisig & R. Michael Roe, 2022. "Species Identification of Caterpillar Eggs by Machine Learning Using a Convolutional Neural Network and Massively Parallelized Microscope," Agriculture, MDPI, vol. 12(9), pages 1-11, September.
  17. Mattrand, C. & Bourinet, J.-M., 2014. "The cross-entropy method for reliability assessment of cracked structures subjected to random Markovian loads," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 171-182.
  18. Alibrandi, Umberto, 2014. "A response surface method for stochastic dynamic analysis," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 44-53.
  19. Wada, Kentaro & Usui, Kento & Takigawa, Tsubasa & Kuwahara, Masao, 2018. "An optimization modeling of coordinated traffic signal control based on the variational theory and its stochastic extension," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 907-925.
  20. Nguyen, Hoa T.M. & Chow, Andy H.F. & Ying, Cheng-shuo, 2021. "Pareto routing and scheduling of dynamic urban rail transit services with multi-objective cross entropy method," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
  21. R. Y. Rubinstein, 2005. "A Stochastic Minimum Cross-Entropy Method for Combinatorial Optimization and Rare-event Estimation," Methodology and Computing in Applied Probability, Springer, vol. 7(1), pages 5-50, March.
  22. Jiaqiao Hu & Michael C. Fu & Steven I. Marcus, 2007. "A Model Reference Adaptive Search Method for Global Optimization," Operations Research, INFORMS, vol. 55(3), pages 549-568, June.
  23. Liang Huang & Juanjuan Zhu & Mulan Qiu & Xiaoxiang Li & Shasha Zhu, 2022. "CA-BASNet: A Building Extraction Network in High Spatial Resolution Remote Sensing Images," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
  24. Jessica Pesantez-Narvaez & Montserrat Guillen & Manuela Alcañiz, 2019. "Predicting Motor Insurance Claims Using Telematics Data—XGBoost versus Logistic Regression," Risks, MDPI, vol. 7(2), pages 1-16, June.
  25. Kin-Ping Hui, 2011. "Cooperative Cross-Entropy method for generating entangled networks," Annals of Operations Research, Springer, vol. 189(1), pages 205-214, September.
  26. Reuven Y. Rubinstein, 2006. "How Many Needles are in a Haystack, or How to Solve #P-Complete Counting Problems Fast," Methodology and Computing in Applied Probability, Springer, vol. 8(1), pages 5-51, March.
  27. Mathieu Balesdent & Jérôme Morio & Loïc Brevault, 2016. "Rare Event Probability Estimation in the Presence of Epistemic Uncertainty on Input Probability Distribution Parameters," Methodology and Computing in Applied Probability, Springer, vol. 18(1), pages 197-216, March.
  28. Alexander Weissman, 2013. "Optimizing information using the EM algorithm in item response theory," Annals of Operations Research, Springer, vol. 206(1), pages 627-646, July.
  29. Ad Ridder & Bruno Tuffin, 2012. "Probabilistic Bounded Relative Error Property for Learning Rare Event Simulation Techniques," Tinbergen Institute Discussion Papers 12-103/III, Tinbergen Institute.
  30. Tai-Yu Ma & Jean-Patrick Lebacque, 2012. "Dynamic System Optimal Routing In Multimodal Transit Network," Working Papers hal-00740347, HAL.
  31. Wyean Chan & Ger Koole & Pierre L'Ecuyer, 2014. "Dynamic Call Center Routing Policies Using Call Waiting and Agent Idle Times," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 544-560, October.
  32. Sahar Abbas & Fahimeh Moosavi, 2012. "Finding shortest path in static networks: using a modified algorithm," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 1(1), pages 29-34, January.
  33. Tran, Cong Quoc & Keyvan-Ekbatani, Mehdi & Ngoduy, Dong & Watling, David, 2021. "Stochasticity and environmental cost inclusion for electric vehicles fast-charging facility deployment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
  34. Zheng Peng & Donghua Wu & Quan Zheng, 2013. "A Level-Value Estimation Method and Stochastic Implementation for Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 156(2), pages 493-523, February.
  35. Xi Chen & Enlu Zhou, 2015. "Population model-based optimization," Journal of Global Optimization, Springer, vol. 63(1), pages 125-148, September.
  36. Kun Lin & Steven I. Marcus, 2016. "Cumulative weighting optimization," Journal of Global Optimization, Springer, vol. 65(3), pages 487-512, July.
  37. Mehni, Moien Barkhori & Mehni, Mohammad Barkhori, 2023. "Reliability analysis with cross-entropy based adaptive Markov chain importance sampling and control variates," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
  38. Jiang, Yubo & Zhu, Yunfang & Du, Xin & Jin, Tao, 2019. "The implicit network inferred from users’ residences and workplaces enhancing collaborative recommendation on smartphones," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
  39. Bismut, Elizabeth & Straub, Daniel, 2021. "Optimal adaptive inspection and maintenance planning for deteriorating structural systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
  40. Papaioannou, Iason & Geyer, Sebastian & Straub, Daniel, 2019. "Improved cross entropy-based importance sampling with a flexible mixture model," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
  41. Lvyang Qiu & Shuyu Li & Yunsick Sung, 2021. "3D-DCDAE: Unsupervised Music Latent Representations Learning Method Based on a Deep 3D Convolutional Denoising Autoencoder for Music Genre Classification," Mathematics, MDPI, vol. 9(18), pages 1-17, September.
  42. Wu, Xin & Nie, Lei & Xu, Meng, 2017. "Robust fuzzy quality function deployment based on the mean-end-chain concept: Service station evaluation problem for rail catering services," European Journal of Operational Research, Elsevier, vol. 263(3), pages 974-995.
  43. Ferdinand Bollwein & Stephan Westphal, 2022. "Oblique decision tree induction by cross-entropy optimization based on the von Mises–Fisher distribution," Computational Statistics, Springer, vol. 37(5), pages 2203-2229, November.
  44. Zhou, Yuekuan & Zheng, Siqian, 2020. "Climate adaptive optimal design of an aerogel glazing system with the integration of a heuristic teaching-learning-based algorithm in machine learning-based optimization," Renewable Energy, Elsevier, vol. 153(C), pages 375-391.
  45. Enlu Zhou & Xi Chen, 2013. "Sequential Monte Carlo simulated annealing," Journal of Global Optimization, Springer, vol. 55(1), pages 101-124, January.
  46. Xianmin Wang & Xinlong Zhang & Jia Bi & Xudong Zhang & Shiqiang Deng & Zhiwei Liu & Lizhe Wang & Haixiang Guo, 2022. "Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning," IJERPH, MDPI, vol. 19(21), pages 1-26, October.
  47. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
  48. Turati, Pietro & Pedroni, Nicola & Zio, Enrico, 2016. "Advanced RESTART method for the estimation of the probability of failure of highly reliable hybrid dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 117-126.
  49. Price, David J. & Bean, Nigel G. & Ross, Joshua V. & Tuke, Jonathan, 2018. "An induced natural selection heuristic for finding optimal Bayesian experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 112-124.
  50. Zheng Peng & Donghua Wu & Wenxing Zhu, 2016. "The robust constant and its applications in random global search for unconstrained global optimization," Journal of Global Optimization, Springer, vol. 64(3), pages 469-482, March.
  51. Bin Liu, 2017. "Posterior exploration based sequential Monte Carlo for global optimization," Journal of Global Optimization, Springer, vol. 69(4), pages 847-868, December.
  52. Akimoto, Youhei & Auger, Anne & Hansen, Nikolaus, 2022. "An ODE method to prove the geometric convergence of adaptive stochastic algorithms," Stochastic Processes and their Applications, Elsevier, vol. 145(C), pages 269-307.
  53. Simon L. Dürr & Andrea Levy & Ursula Rothlisberger, 2023. "Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  54. Anastasia Spiliopoulou & Ioannis Papamichail & Markos Papageorgiou & Yannis Tyrinopoulos & John Chrysoulakis, 2017. "Macroscopic traffic flow model calibration using different optimization algorithms," Operational Research, Springer, vol. 17(1), pages 145-164, April.
  55. Xiaojiang Tang & Wenhao Zhao & Junwei Guo & Baoxia Li & Xin Liu & Yuan Wang & Feng Huang, 2023. "Recognition of Plasma-Treated Rice Based on 3D Deep Residual Network with Attention Mechanism," Mathematics, MDPI, vol. 11(7), pages 1-18, March.
  56. Huang, Zhenzhen & Kwok, Yue Kuen & Xu, Ziqing, 2024. "Efficient algorithms for calculating risk measures and risk contributions in copula credit risk models," Insurance: Mathematics and Economics, Elsevier, vol. 115(C), pages 132-150.
  57. Marco Caserta & Stefan Voß, 2016. "A corridor method based hybrid algorithm for redundancy allocation," Journal of Heuristics, Springer, vol. 22(4), pages 405-429, August.
  58. Da, Fang & Kou, Gang & Peng, Yi, 2022. "Deep learning based dual encoder retrieval model for citation recommendation," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
  59. Rishang Long & Jianhua Zhang, 2016. "Risk Assessment Method of UHV AC/DC Power System under Serious Disasters," Energies, MDPI, vol. 10(1), pages 1-13, December.
  60. El Masri, Maxime & Morio, Jérôme & Simatos, Florian, 2021. "Improvement of the cross-entropy method in high dimension for failure probability estimation through a one-dimensional projection without gradient estimation," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  61. Deng, Xiangtian & Zhang, Yi & Jiang, Yi & Zhang, Yi & Qi, He, 2024. "A novel operation method for renewable building by combining distributed DC energy system and deep reinforcement learning," Applied Energy, Elsevier, vol. 353(PB).
  62. Alexander L Krall & Michael E Kuhl & Shanchieh J Yang, 2022. "Estimation of cyber network risk using rare event simulation," The Journal of Defense Modeling and Simulation, , vol. 19(1), pages 37-55, January.
  63. Hao Su & Qun Niu & Zhile Yang, 2023. "Optimal Power Flow Using Improved Cross-Entropy Method," Energies, MDPI, vol. 16(14), pages 1-33, July.
  64. Satyajith Amaran & Nikolaos V. Sahinidis & Bikram Sharda & Scott J. Bury, 2016. "Simulation optimization: a review of algorithms and applications," Annals of Operations Research, Springer, vol. 240(1), pages 351-380, May.
  65. Zhang, Yali & Shang, Pengjian, 2019. "Multivariate multiscale distribution entropy of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 72-80.
  66. Dirk P. Kroese & Sergey Porotsky & Reuven Y. Rubinstein, 2006. "The Cross-Entropy Method for Continuous Multi-Extremal Optimization," Methodology and Computing in Applied Probability, Springer, vol. 8(3), pages 383-407, September.
  67. Caballero, Rafael & Hernández-Díaz, Alfredo G. & Laguna, Manuel & Molina, Julián, 2015. "Cross entropy for multiobjective combinatorial optimization problems with linear relaxations," European Journal of Operational Research, Elsevier, vol. 243(2), pages 362-368.
  68. Ali Kadhem, Athraa & Abdul Wahab, Noor Izzri & Aris, Ishak & Jasni, Jasronita & Abdalla, Ahmed N., 2017. "Computational techniques for assessing the reliability and sustainability of electrical power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1175-1186.
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