Hao Wang

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 105

Top Venues

Publications

Hao Wang, Angel E. Rodriguez-Fernandez, Lourdes Uribe, André H. Deutz, Oziel Cortés-Piña, Oliver Schütze
A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms. CoRR (2024)
Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang
Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder. CoRR (2024)
Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck
Large-scale Benchmarking of Metaphor-based Optimization Heuristics. CoRR (2024)
Hao Wang, Jianqi Hu, Andrea Morandi, Alfonso Nardi, Fei Xia, Xuanchen Li, Romolo Savo, Qiang Liu, Rachel Grange, Sylvain Gigan
Large-scale photonic computing with nonlinear disordered media. Nat. Comput. Sci. 4 (6) (2024)
Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang
Transfer Learning of Surrogate Models via Domain Affine Transformation. GECCO (2024)
Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. GECCO (2024)
Hao Wang, Jianqi Hu, YoonSeok Baek, Kohei Tsuchiyama, Malo Joly, Qiang Liu, Sylvain Gigan
Optical next generation reservoir computing. CoRR (2024)
Zhengtian Ai, Ingo Heinle, Christian Schelske, Hao Wang, Peter Krause, Thomas Bäck
Classification-based process parameter recommendation in sheet metal forming. J. Ind. Inf. Integr. 34 (2023)
Thomas H. W. Bäck, Anna V. Kononova, Bas van Stein, Hao Wang, Kirill A. Antonov, Roman T. Kalkreuth, Jacob de Nobel, Diederick Vermetten, Roy de Winter, Furong Ye
Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. Evol. Comput. 31 (2) (2023)
Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CEC (2023)
Jiajie Fan, Laure Vuaille, Thomas Bäck, Hao Wang
On the Noise Scheduling for Generating Plausible Designs with Diffusion Models. CoRR (2023)
Waheeda Saib, Xavier Bonet-Monroig, Vedran Dunjko, Ivano Tavernelli, Thomas Bäck, Hao Wang
Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry. QCE (2023)
Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko
Application of quantum-inspired generative models to small molecular datasets. QCE (2023)
Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion (2023)
André H. Deutz, Michael Emmerich, Hao Wang
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. EMO (2023)
Hao Wang, Kaifeng Yang, Michael Affenzeller, Michael Emmerich
Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. CoRR (2022)
André H. Deutz, Michael T. M. Emmerich, Hao Wang
The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. CoRR (2022)
Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
A Systematic Approach to Analyze the Computational Cost of Robustness in Model-Assisted Robust Optimization. PPSN (1) (2022)
Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. PPSN (1) (2022)
Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics. ACM Trans. Evol. Learn. Optim. 2 (1) (2022)
Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. GECCO Companion (2022)
Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. GECCO Companion (2022)
Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck
Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. GECCO (2022)
Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye
Benchmarking and analyzing iterative optimization heuristics with IOH profiler. GECCO Companion (2022)
Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. CoRR (2022)
Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. IEEE Trans. Evol. Comput. 26 (6) (2022)
Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck
Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms. CoRR (2022)
Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr
Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. PPSN (1) (2022)
Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features. CoRR (2022)
Dominik Schröder, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points. CoRR (2022)
Duc Anh Nguyen, Jiawen Kong, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Anna V. Kononova, Thomas Bäck
Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems. DSAA (2021)
Jacob de Nobel, Hao Wang, Thomas Bäck
Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. CoRR (2021)
Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. CoRR (2021)
Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
A new acquisition function for robust Bayesian optimization of unconstrained problems. GECCO Companion (2021)
Rick Boks, Anna V. Kononova, Hao Wang
Quantifying the impact of boundary constraint handling methods on differential evolution. GECCO Companion (2021)
Hao Wang, Carlos Ignacio Hernández Castellanos, Tome Eftimov
On Statistical Analysis of MOEAs with Multiple Performance Indicators. EMO (2021)
Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Comput. Oper. Res. 136 (2021)
Jacob de Nobel, Hao Wang, Thomas Bäck
Explorative data analysis of time series based algorithm features of CMA-ES variants. GECCO (2021)
Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules. CoRR (2021)
Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
Is there Anisotropy in Structural Bias? CoRR (2021)
Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck
Bayesian neural architecture search using a training-free performance metric. Appl. Soft Comput. 106 (2021)
Charles Moussa, Hao Wang, Henri Calandra, Thomas Bäck, Vedran Dunjko
Tabu-Driven Quantum Neighborhood Samplers. EvoCOP (2021)
Rick Boks, Anna V. Kononova, Hao Wang
Quantifying the Impact of Boundary Constraint Handling Methods on Differential Evolution. CoRR (2021)
Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
Can Single Solution Optimisation Methods Be Structurally Biased? CEC (2020)
Diederick Vermetten, Hao Wang, Thomas Bäck, Carola Doerr
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. GECCO (2020)
Ullah Ullah, Zhao Xu, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models. IJCNN (2020)
Víctor Adrián Sosa-Hernández, Oliver Schütze, Hao Wang, André H. Deutz, Michael Emmerich
The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. IEEE Trans. Cybern. 50 (5) (2020)
Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck
Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. PPSN (2) (2020)
Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke
Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. SSCI (2020)
Bas van Stein, Hao Wang, Thomas Bäck
Neural Network Design: Learning from Neural Architecture Search. CoRR (2020)
Hao Wang, Carola Doerr, Ofer M. Shir, Thomas Bäck
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion (2020)
Rick Boks, Hao Wang, Thomas Bäck
A Modular Hybridization of Particle Swarm Optimization and Differential Evolution. CoRR (2020)
Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. PPSN (1) (2020)
Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter
Squirrel: A Switching Hyperparameter Optimizer. CoRR (2020)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck
Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. 50 (3) (2020)
Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. CoRR (2020)
Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck
Bayesian Neural Architecture Search using A Training-Free Performance Metric. CoRR (2020)
Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck
Benchmarking a $(μ+λ)$ Genetic Algorithm with Configurable Crossover Probability. CoRR (2020)
Marios Kefalas, Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck
Automated Machine Learning for the Classification of Normal and Abnormal Electromyography Data. IEEE BigData (2020)
Milan Koch, Hao Wang, Robert Bürgel, Thomas Bäck
Towards Data-driven Services in Vehicles. VEHITS (2020)
Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case. CoRR (2020)
Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR (2020)
Hao Wang, Carlos Ignacio Hernández Castellanos, Tome Eftimov
On Statistical Analysis of MOEAs with Multiple Performance Indicators. CoRR (2020)
Sibghat Ullah, Duc Anh Nguyen, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization. SSCI (2020)
Rick Boks, Hao Wang, Thomas Bäck
A modular hybridization of particle swarm optimization and differential evolution. GECCO Companion (2020)
Bas van Stein, Hao Wang, Thomas Bäck
Neural Network Design: Learning from Neural Architecture Search. SSCI (2020)
Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. GECCO (2020)
Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
Can Compact Optimisation Algorithms Be Structurally Biased? PPSN (1) (2020)
Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
Benchmarking discrete optimization heuristics with IOHprofiler. Appl. Soft Comput. 88 (2020)
Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich
Search Dynamics on Multimodal Multiobjective Problems. Evol. Comput. 27 (4) (2019)
Sina Däubener, Sebastian Schmitt, Hao Wang, Peter Krause, Thomas Bäck
Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. ICDM (2019)
Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck
Automated Machine Learning for EEG-Based Classification of Parkinson's Disease Patients. IEEE BigData (2019)
Teddy Etoeharnowo, Koen Castelein, Hao Wang, Thomas Bäck
Switching Between Swarm Optimization Algorithms During a Run: An Empirical Study. SSCI (2019)
Hao Wang, Michael Emmerich, Thomas Bäck
Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies. Evol. Comput. 27 (4) (2019)
Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. SSCI (2019)
Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
Benchmarking Discrete Optimization Heuristics with IOHprofiler. CoRR (2019)
Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss
On the potential of evolution strategies for neural network weight optimization. GECCO (Companion) (2019)
Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. CoRR (2019)
Hao Wang, Yitan Lou, Thomas Bäck
Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution. CEC (2019)
Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
Benchmarking discrete optimization heuristics with IOHprofiler. GECCO (Companion) (2019)
Bas van Stein, Hao Wang, Thomas Bäck
Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. IJCNN (2019)
Borja Calvo, Ofer M. Shir, Josu Ceberio, Carola Doerr, Hao Wang, Thomas Bäck, José Antonio Lozano
Bayesian performance analysis for black-box optimization benchmarking. GECCO (Companion) (2019)
Milan Koch, Hao Wang, Thomas Bäck
Machine Learning for Predicting the Damaged Parts of a Low Speed Vehicle Crash. ICDIM (2018)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck
A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) (2018)
Bas van Stein, Hao Wang, Thomas Bäck
Automatic Configuration of Deep Neural Networks with EGO. CoRR (2018)
Hao Wang, Thomas Bäck
Ranking empirical cumulative distribution functions using stochastic and pareto dominance. GECCO (Companion) (2018)
Hao Wang, Michael Emmerich, Thomas Bäck
Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. CEC (2018)
Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck
IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. CoRR (2018)
Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck
Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. GECCO (2018)
Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck
Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling (1+λ) EA Variants on OneMax and LeadingOnes. CoRR (2018)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck
Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR (2017)
Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck
A new acquisition function for Bayesian optimization based on the moment-generating function. SMC (2017)
Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck
Algorithm configuration data mining for CMA evolution strategies. GECCO (2017)
Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck
Time complexity reduction in efficient global optimization using cluster kriging. GECCO (2017)
Sheir Yarkoni, Hao Wang, Aske Plaat, Thomas Bäck
Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning. QTOP@NetSys (2017)
Hao Wang, André H. Deutz, Thomas Bäck, Michael Emmerich
Hypervolume Indicator Gradient Ascent Multi-objective Optimization. EMO (2017)
Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck
Evolving the Structure of Evolution Strategies. CoRR (2016)
Hao Wang, Michael T. M. Emmerich, Thomas Bäck
Balancing risk and expected gain in kriging-based global optimization. CEC (2016)
Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN (2016)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck
Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hao Wang