Hao Wang
Assistant Professor
- Name
- Dr. H. Wang
- Telephone
- +31 71 527 4799
- h.wang@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-4933-5181
Hao Wang about Machine Learning
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- Science
- Leiden Inst of Advanced Computer Science
- Bonet-Monroig X., Wang H., Vermetten D.L., Senjean B., Moussa C., Bäck T.H.W., Dunjko V. & O'Brien T.E. (2023), Performance comparison of optimization methods on variational quantum algorithms, Physical Review A 107(3): 032407.
- Ullah S., Wang H., Menzel S., Sendhoff B. & Bäck T.H.W. (2022), A systematic approach to analyze the computational cost of robustness in model-assisted robust optimization: a systematic approach to analyze the computational cost. In: Rudolph G., Kononova A.V., Aguirre H., Kerschke P., Ochoa G. & Tušar T. (Eds.) Lecture notes in computer science (LNCS). no. 13398 Cham: Springer. 63-75.
- Moussa C., Wang H., Bäck T.H.W. & Dunjko V (2022), Unsupervised strategies for identifying optimal parameters in Quantum Approximate Optimization Algorithm, EPJ Quantum Technology 9: 11.
- Wang H., Vermetten D., Ye F., Doerr C. & Bäck T.H.W. (2022), IOHanalyzer: detailed performance analyses for iterative optimization heuristics, ACM Transactions on Evolutionary Learning and Optimization 2(1): 3.
- Ye F., Doerr C., Wang H. & Bäck T.H.W. (2022), Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. In: Fieldsend J.E. (Ed.) GECCO '22: proceedings of the genetic and evolutionary computation conference companion. New York, NY, United States: Association for Computing Machinery . 51-52.
- Ye F., Doerr C., Wang H. & Bäck T.H.W. (2022), Automated configuration of genetic algorithms by tuning for anytime performance, IEEE Transactions on Evolutionary Computation 26(6): 1526-1538.
- Wang H., Vermetten D., Ye F., Doerr C. & Bäck T.H.W (2022), IOHanalyzer: detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. In: Fieldsend J.E. (Ed.) GECCO '22: proceedings of the genetic and evolutionary computation conference companion. New York, NY, United States: Association for Computing Machinery . 49-50.
- Grimme C., Kerschke P., Aspar P., Trautmann H., Preuss M., Deutz A.H., Wang H. & Emmerich M.T.M. (2021), Peeking beyond peaks: challenges and research potentials of continuous multimodal multi-objective optimization, Computers and Operations Research 136: 105489.
- Vermetten D., Kononova A.V., Caraffini F., Wang H. & Bäck T.H.W. (2021), Is there anisotropy in structural bias?. In: Krawiec K. (Ed.) Genetic and Evolutionary Computation Conference, Companion Volume. Lille, France: ACM. 1243–1250.
- Nobel J.P. de, Vermetten D., Wang H., Doerr C. & Bäck T.H.W. (2021), Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. In: Krawiec K. (Ed.) Genetic and Evolutionary Computation Conference, Companion Volume. Lille, France: ACM. 1375-1384.
- Ullah S., Wang H., Menzel S, Sendhoff B. & Bäck T.H.W. (2021), A new acquisition function for robust Bayesian optimization of unconstrained problems. In: Chicano F. (Ed.) Gecco '21: proceedings of the genetic and evolutionary computation conference companion. New York: ACM. 1344-1345.
- Boks R., Kononova A.V. & Wang H. (2021), Quantifying the impact of boundary constraint handling methods on differential evolution. In: Chicano F. (Ed.) GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference. New York, U.S.A.: ACM. 1199-1207.
- Geraedts V.J., Koch M., Kuiper R., Kefalas M., Bäck T.H.W., Hilten J.J., Wang H., Middelkoop H.A.M., Gaag N.A., Contarino M.F. & Tannemaat M.R. (2021), Preoperative electroencephalography‐based machine learning predicts cognitive deterioration after subthalamic deepbrain stimulation, Movement Disorders 36(10): 2324-2334.
- Ai Z., Ingo H., Schelske C.,Wang H., Krause P. & Bäck T.H.W. (2021), A classification-based solution for recommending process parameters of production processes without quality measures, Procedia Computer Science 180: 600-607.
- Camero Unzueta A., Wang H., Alba E. & Bäck T.H.W. (2021), Bayesian neural architecture search using a training-free performance metric, Applied Soft Computing 106: 107356.
- Nobel J.P. de, Wang H. & Bäck T.H.W. (2021), Explorative data analysis of time series based algorithm features of CMA-ES variants. In: Chicano F. (Ed.) GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference.: ACM. 510-518.
- Nguyen D.A., Kong J., Wang H., Menzel S., Sendhoff B., Kononova A.V. & Bäck T.H.W. (2021), Improved automated CASH optimization with tree parzen estimators for class imbalance problems. In: 2021 IEEE 8th international conference on data science and advanced analytics (DSAA).: Institute of Electrical and Electronics Engineers (IEEE). 1-9.
- Geraedts V.J., Koch M., Contarino M.F., Middelkoop H.A.M., Wang H. Hilten J.J. van, Bäck T.H.W. & Tannemaat M.R. (2021), Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson’s Disease, Clinical Neurophysiology 132(5): 1041-1048.
- Thill M., Konen W., Wang H. & Bäck T.H.W. (2021), Temporal convolutional autoencoder for unsupervised anomaly detection in time series, Applied Soft Computing 112: 107751.
- Stein N. van, Wang H. & Bäck T.H.W. (2020), Neural network design: learning from Neural Architecture Search, 2020 IEEE Symposium series on computational intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020: IEEE. 1341-1349.
- Ye F., Wang H., Doerr C. & Bäck T.H.W. (2020), Benchmarking a (μ+λ) genetic algorithm with configurable crossover probability. In: Bäck T.H.W., Preuss M., Deutz A., Wang H., Doerr C., Emmerich M.T.M. & Trautman H. (Eds.) Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020. no. 12270 Cham: Springer. 699-713.
- Kononova A.V., Caraffini F., Wang H. & Bäck T.H.W. (2020), Can compact optimisation algorithms be structurally biased?. Bäck T.H.W., Preuss M., Deutz A., Wang H., Doerr C., Emmerich M.T.M. & Trautmann H. (Eds.), Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020 (16th International Conference on Parallel Problem Solving from Nature) 5 September 2020 - 9 September 2020 no. 12269. Cham: Springer . 229-242.
- Wang H., Doerr C., Shir O.M. & Bäck T.H.W. (2020), Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. In: GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion.: ACM. 1043-1054.
- Koch M., Geraedts V., Wang H., Tannemaat M. & Bäck T. (2019), Automated Machine Learning for EEG-Based Classification of Parkinson’s Disease Patients, 2019 IEEE International Conference on Big Data (Big Data). IEEE International Conference on Big Data (Big Data) 9 December 2019 - 12 December 2019: IEEE. 4845-4852.
- Kononova A.V., Caraffini F., Wang H. & Bäck T.H.W. (2020), Can single solution optimisation methods be structurally biased?, 2020 IEEE Congress on evolutionary computation (CEC). 2020 IEEE Congress on Evolutionary Computation (CEC) 19 July 2020 - 24 July 2020. Preprints: IEEE. 1-9.
- Boks R., Wang H. & Bäck T. (2020), A modular hybridization of particle swarm optimization and differential evolution, GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO 2020) 8 July 2020 - 12 July 2020. New York, NY, USA: Association for Computing Machinery. 1418–1425.
- Kefalas M., Koch M.., Geraedts V.J., Wang H., Tannemaat M. & Bäck T.H.W. (2020), Automated Machine Learning for the Classification of Normal and Abnormal Electromyography data. 2020 IEEE International Conference on Big Data (IEEE BigData 2020) 10 December 2020 - 13 December 2020: IEEE.
- Ullah S., Xu Z., Wang H., Menzel S., Sendhoff B. & Bäck T. (2020), Exploring clinical time series forecasting with meta-features in variational recurrent models, 2020 International Joint Conference on Neural Networks (IJCNN). 2020 International Joint Conference on Neural Networks (IJCNN) 19 July 2020 - 24 July 2020: IEEE. 1-9.
- Ullah S., Nguyen D.A., Wang H., Menzelx S., Sendhoff B. & Bäck T.H.W. (2020), Exploring dimensionality reduction techniques for efficient surrogate-assisted optimization. IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020.
- Raponi E., Wang H., Bujny M., Boria S. & Doerr C. (2020), High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. Bäck T., Preuss M., Deutz A., Wang H., Doerr C., Emmerich M. & Trautmann H. (Eds.), Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020. Lecture Notes in Computer Science. PPSN 2020 (16th International Conference on Parallel Problem Solving from Nature) 5 September 2020 - 9 September 2020 no. 12269. Cham: Springer. 169-183.
- Vermetten D.L., Wang H., Doerr C. & Bäck T.H.W. (2020), Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. In: GECCO '20: Genetic and evolutionary computation conference.: ACM. 903-912.
- Prager R.P., Traumann H., Wang H., Bäck T.H.W. & Kerschke P. (2020), Per-instance configuration of the modularized CMA-ES by means of classifier chains and exploratory landscape analysis, 2020 IEEE Symposium series on computational intelligence (SSCI). IEEE Symposium Series on Computational Intelligence (SSCI) 1 December 2020 - 4 December 2020: IEEE. 996-1003.
- Vermetten D.L., Wang H., Doerr C. & Bäck T.H.W. (2020), Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. arXiv no. 1912.05899. [working paper].
- Moussa C., Wang H., Calandra H., Bäck T.H.W. & Dunjko V. (2020), Tabu-driven quantum neighborhood samplers. Zarges C. & Verel S. (Eds.), Evolutionary computation in combinatorial optimization. 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021 7 April 2021 - 9 April 2021. arXiv no. 12692. Cham: Springer. 100-119.
- Hernández V.A., Schütze O., Wang H., Deutz A.H. & Emmerich M.T.M. (2020), The set-based hypervolume Newton method for bi-objective optimization, IEEE Transactions on Cybernetics 50(5): 2186-2196.
- Koch M., Wang H., Bürgel R. & Bäck T.H.W. (2020), Towards Data-Driven Services in Vehicles. 6th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2020, Prague (*online-conference due to COVID-19). 2 May 2020 - 4 May 2020. [conference poster].
- Vermetten D.L., Wang H., Bäck T.H.W. & Doerr C. (2020), Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case, GECCO '20: Proceedings of the 2020 genetic and evolutionary computation conference companion. Genetic and Evolutionary Computation Conference (GECCO 2020) 8 July 2020 - 12 July 2020. New York, U.S.A.: Association for Computing Machinery. 654-662.
- Doerr C., Ye F., Horesh N., Wang H., Shir O.M. & Bäck T.H.W. (2020), Benchmarking discrete optimization heuristics with IOHprofiler, Applied Soft Computing 88: 106027.
- Stein B. van, Wang H., Kowalczyk W.J., Emmerich M.T.M. & Bäck T.H.W. (2019), Cluster-based Kriging approximation algorithms for complexity reduction, Applied Intelligence : .
- Ullah S. Wang H. Menzel S. Sendhoff B. Bäck T.H.W. (2019), An empirical comparison of meta-modeling techniques for robust design optimization. 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 December 2019 - 9 December 2019. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. 819-828.
- Stein B. van, Wang H. & Bäck T.H.W. (2019), Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization, 2019 International Joint Conference on Neural Networks (IJCNN). 2019 International Joint Conference on Neural Networks (IJCNN) 14 July 2019 - 19 July 2019. Budapest, Hungary, Hungary: IEEE. 1-7.
- Calvo B., Shir O.M., Ceberio J., Doerr C., Wang H. & Bäck T.H.W. (2019), Bayesian Performance Analysis for Black-box Optimization Benchmarking, Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2019 13 July 2019 - 17 July 2019: ACM. 1789-1797.
- Doerr C., Ye F., Horesh N., Wang H., Shir O.M. & Bäck T.H.W. (2019), Benchmarking Discrete Optimization Heuristics with IOHprofiler, Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2019 13 July 2019 - 17 July 2019: ACM. 1798--1806.
- Yarkoni S., Wang H., Plaat A. & Bäck T.H.W. (2019), Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning. Feld S. & Linnhoff-Popien C. (Eds.), Quantum Technology and Optimization Problems. QTOP 2019 18 March 2019 - 21 March 2019 no. LNCS 11413. Cham: Springer International Publishing. 157-168.
- Wang H., Yitan L. & Bäck T.H.W. (2019), Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution, 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE Congress on Evolutionary Computation (CEC) 2019 10 June 2019 - 13 June 2019: IEEE. 2649-2656.
- Wang H., Emmerich M.T.M. & Bäck T.H.W. (2019), Mirrored orthogonal sampling for covariance matrix adaptation evolution strategies, Evolutionary Computation 27(4): 699-725.
- Wang H., Bäck T.H.W., Plaat A., Emmerich M.T.M. & Preuss M. (2019), On the potential of evolution strategies for neural network weight optimization. Lopez-Ibanez M., Auger A. & Stützle T. (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2019 13 July 2019 - 17 July 2019: ACM. 191-192.
- Etoeharnowo T., Castelein K., Wang H. & Bäck T.H.W. (2019), Switching Between Swarm Optimization Algorithms During a Run: An Empirical Study, 2019 IEEE Symposium on Computational Intelligence (SSCI). 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 December 2019 - 9 December 2019: IEEE. 2295-2302.
- Wang H., Emmerich M.T.M. & Bäck T.H.W. (2019), Towards Self-Adaptive Efficient Global Optimization, AIP Conference Proceedings. LeGO - 14th International Global Optimization Workshop 18 September 2018 - 21 September 2018 no. 2070: AIP Publishing. 020056.
- Wang H. (1 November 2018), Stochastic and deterministic algorithms for continuous black-box optimization (Dissertatie. Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University). Supervisor(s) and Co-supervisor(s): Bäck T.H.W., Emmerich M.T.M.
- Kerschke P., Wang H., Preuss M., Grimme G., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2019), Search Dynamics on Multimodal Multi-Objective Problems, Evolutionary Computation 27(4): 577-609.
- Blom K. van der, Boonstra S., Wang H., Hofmeyer H. & Emmerich M.T.M. (2018), Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent. In: Trujillo L., Schütze O., Maldonado Y. & Valle P. (Eds.), Numerical and Evolutionary Optimization – NEO 2017. Studies in Computational Intelligence no. 785. Cham: Springer. 62-86.
- Doerr C., Ye F., Rijn S.J. van, Wang H. & Bäck T.H.W. (2018), Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling (1+λ) EA Variants on OneMax and LeadingOnes. Aguirre H. (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '18). GECCO 2018 15 July 2018 - 19 July 2018. Kyoto, Japan: ACM. 951-958.
- Emmerich M.T.M., Shir M.O. & Wang H. (2018), Evolution Strategies. In: Martí R., Panos P. & Resende G.C.M. (Eds.), Handbook of Heuristics. Cham: Springer International Publishing. 1-31.
- Stein B. van, Wang H., Kowalczyk W.J. & Bäck T.H.W. (2018), A Novel Uncertainty Quantification Method for Efficient Global Optimization. Medina J., Ojeda-Aciego M., Verdegay J.L., Perfilieva I., Bouchon-Meunier B. & Yager R.R. (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications - 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III. IPMU 2018 : 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems 11 June 2018 - 15 June 2018 no. Communications in Computer and Information Science, volume 855. Cham: Springer. 480-491.
- Stein B. van, Wang H. & Bäck T.H.W. (2018), Automatic Configuration of Deep Neural Networks with EGO.
- Wang H., Emmerich M.T.M. & Bäck T.H.W. (2018), Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization, 2018 IEEE Congress on Evolutionary Computation (CEC 2018). 2018 IEEE Congress on Evolutionary Computation (CEC) 8 July 2018 - 13 July 2018: IEEE. 1-8.
- Doerr C., Wang H., Ye F., Rijn S.J. van & Bäck T.H.W. (2018), IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics.
- Koch M., Wang H. & Bäck T.H.W. (2018), Machine Learning for Predicting the Damaged Parts of a Low Speed Vehicle Crash, 2018 Thirteenth International Conference on Digital Information Management. International Conference on Digital Information Management (ICDIM) 24 September 2018 - 26 September 2019. Berlin, Germany: IEEE Xplore. 179-184.
- Wang H., Bäck T.H.W. & Emmerich M.T.M. (2018), Multi-point Efficient Global Optimization Using Niching Evolution Strategy. Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L. & Luchian H. (Eds.), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. The EVOLVE 2015 International Conference 18 June 2015 - 24 June 2015 no. Advances in Intelligent Systems and Computing, volume 674. Cham: Springer. 146-162.
- Wang H. & Bäck T.H.W. (2018), Ranking Empirical Cumulative Distribution Functions using Stochastic and Pareto Dominance. Aguirre H. (Ed.), GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2018 15 July 2018 - 19 July 2018. New York, NY, USA: ACM. 257-258.
- Rijn S.J. van, Wang H., Stein B. van & Bäck T.H.W. (2017), Algorithm configuration data mining for CMA evolution strategies, GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO 2017) 15 July 2017 - 19 July 2017. New York: ACM. 737-744.
- Wang H., Stein B. van, Emmerich M.T.M. & Bäck T.H.W. (2017), Time complexity reduction in efficient global optimization using cluster kriging, GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference (GECCO 2017) 15 July 2017 - 19 July 2017. New York: ACM. 889-896.
- Kerschke P., Wang H., Preuss M., Grimme C., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2017), Towards analyzing multimodality of multiobjective landscapes: PPSN 2016 best paper award. [other].
- Wang H., Stein B. van, Emmerich M.T.M. & Bäck T.H.W. (2017), A New Acquisition Function for Bayesian optimization based on the moment-generating function. Wang Hao, Stein B. van, Emmerich Michael T.M. & Bäck T.H.W. (Eds.), 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) 5 October 2017 - 8 October 2017. Banff, AB, Canada: IEEE. 507-512.
- Wang H., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2017), Hypervolume Indicator Gradient Ascent Multi-objective Optimization. Trautmann H., Rudolph G., Klamroth K., Schütze O., Wiecek M., Jin Y. & Grimme C. (Eds.), Evolutionary Multi-Criterion Optimization. 9th International Conference on Evolutionary Multi-Criterion Optimization 19 March 2017 - 22 March 2017 no. 10173. Cham: Springer International Publishing. 654-669.
- Stein B. van, Leeuwen M. van, Wang H., Purr S., Kreissl S., Meinhardt J. & Bäck T.H.W. (2017), Towards Data Driven Process Control in Manufacturing Car Body Parts, 2016 International Conference on Computational Science and Computational Intelligence CSCI. International Conference on Computational Science and Computational Intelligence (CSCI 2016) 15 December 2016 - 17 December 2016: IEEE CPS.
- Emmerich M.T.M., Yang K., Deutz A.H., Wang H. & Fonseca C.M. (2016), A Multicriteria Generalization of Bayesian Global Optimization. In: Pardalos M.P., Zhigljavsky A. & Zilinskas J. (Eds.), Advances in Stochastic and Deterministic Global Optimization. Optimization and its Applications no. 107. Cham: Springer. 229-243.
- Stein B. van, Hao Wang, Kowalczyk W.J., Emmerich Michael T.M. & Bäck T.H.W. (2016), Fuzzy clustering for Optimally Weighted Cluster Kriging, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Fuzzy Systems, 2016 IEEE 24 June 2016 - 29 June 2016: IEEE. 978-1-5090-0627-4.
- Hao Wang, Ren Y., Deutz A. & Emmerich M.T.M. (2016), On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. In: Schuetze O., Trujillo L., Legrand P. & Maldonado Y. (Eds.), NEO 2015: Results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico. Studies in Computational Intelligence no. Studies in Computational Intelligence 663. Cham: Springer International Publishing. 175-203.
- Hao Wang, Emmerich Michael T.M. & Bäck T. (2016), Balancing Risk and Expected Gain in Kriging-based Global Optimization, 2016 IEEE Congress on Evolutionary Computation (CEC). 2016 IEEE Congress on Evolutionary Computation (CEC) 24 July 2016 - 29 July 2016: IEEE Publishing. 719-727.
- Rijn Sander van, Hao Wang, Leeuwen M. van & Bäck T.H.W. (2016), Evolving the Structure of Evolution Strategies, 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE SSCI 2016 6 December 2016 - 9 December 2016: IEEE Publishing. 1-8.
- Cai F., Wang H., Tang X., Emmerich M.T.M. & Verbeek F.J. (2016), Fuzzy Criteria in Multi-objective Feature Selection for Unsupervised Learning, Procedia Computer Science 102: 51-58.
- Zhang X., Wu J., Wang H., Xiong J. & Yang K. (2016), Optimization of Disintegration Strategy for Multi-edges Complex Networks, Evolutionary Computation (CEC), 2016 IEEE Congress on. : IEEE. 522-528.
- Yang Z., Hao Wang, Yang K., Bäck T. & Emmerich M.T.M. (2016), SMS-EMOA with multiple dynamic reference points, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD),. 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) 13 August 2016 - 15 August 2016: IEEE Publishing. 282-288.
- Kerschke P., Hao Wang, Preuss M., Grimme C., Deutz A., Trautmann H. & Emmerich M.T.M. (2016), Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. Handl J., Hart E., Lewis P.R., López-Ibáñez M., Ochoa G. & Paechter B. (Eds.), Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016 (14th International Conference on Parallel Problem Solving from Nature) 17 September 2016 - 21 September 2016: Springer International Publishing. 962-972.
- Stein B. van, Wang H., Kowalczyk W., Bäck T. & Emmerich M. (2015), Optimally Weighted Cluster Kriging for Big Data Regression. Fromont E., Bie T. de & Leeuwen M. van (Eds.), Advances in Intelligent Data Analysis XIV. 14th International Symposium, IDA 2015 22 October 2015 - 24 October 2015 no. LNCS 9385. Cham: Springer International Publishing. 310-321.
- Wang H., Schwab I. & Emmerich M.T.M. (2015), Comparing Knowledge Representation Forms in Empirical Model Building. Schwab I., Moergestel L. van & Goncalves G. (Eds.), Proceedings of the Fourth International Conference on Intelligent Systems and Application. Intelli 2015. The Fourth International Conference on Intelligent Systems and Applications 11 October 2015 - 16 October 2015. Wilmington, DE, U.S.A.: IARIA. 170-178.
- Hao Wang, Bäck T.H.W. & Emmerich M.T.M. (2015), Multi-point efficient global optimization using Niching Evolution Strategy, Proceedings EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. EVOLVE 2015 18 June 2015 - 24 February 2016: Springer.
- Hao Wang, Emmerich Michael T.M. & Bäck T.H.W. (2014), Mirrored orthogonal sampling with pairwise selection in evolution strategies, Proceedings 29th Annual ACM Symposium on Applied Computing. : ACM. 154-156.
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