Hao Wang - RankMe

146 papers A* 3A 13B 13C 6Misc 3Journal 64Unranked 39

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Center-Outward q-Dominance: A Sample-Computable Proxy for Strong Stochastic Dominance in Stochastic Multi-Objective Optimisation. AAAI Robin van der Laag, Hao Wang, Thomas Bäck, Yingjie Fan
2026	J	`jnl`	Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machines. CoRR Kevin Shen, Susanne Pielawa, Vedran Dunjko, Hao Wang
2026	J	`jnl`	Training deep physical neural networks with local physical information bottleneck. CoRR Hao Wang, Ziao Wang, Xiangpeng Liang, Han Zhao, Jianqi Hu, Junjie Jiang, Xing Fu, Jianshi Tang, Huaqiang Wu, Sylvain Gigan, Qiang Liu
2025	J	`jnl`	A Mesh Is Worth 512 Numbers: Spectral-domain Diffusion Modeling for High-dimension Shape Generation. CoRR Jiajie Fan, Amal Trigui, Andrea Bonfanti, Felix Dietrich, Thomas Bäck, Hao Wang
2025	J	`jnl`	A Multi-Form Optimization Framework for Analog Integrated Circuit Sizing. IEEE Trans. Circuits Syst. I Regul. Pap. Chen Chen, Hongyi Wang, Feng Liang, Thomas Bäck, Hao Wang
2025	J	`jnl`	A Newton Method for Hausdorff Approximations of the Pareto Front Within Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. Hao Wang, Angel E. Rodriguez-Fernandez, Lourdes Uribe, André H. Deutz, Oziel Cortés-Piña, Oliver Schütze
2025	A	`conf`	Abnormal Mutations: Evolution Strategies Don't Require Gaussianity. GECCO Jacob de Nobel, Diederick Vermetten, Hao Wang, Anna V. Kononova, Günter Rudolph, Thomas Bäck
2025	J	`jnl`	Abnormal Mutations: Evolution Strategies Don't Require Gaussianity. CoRR Jacob de Nobel, Diederick Vermetten, Hao Wang, Anna V. Kononova, Günter Rudolph, Thomas Bäck
2025	A	`conf`	An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise. GECCO Catalin-Viorel Dinu, Yash J. Patel, Xavier Bonet-Monroig, Hao Wang
2025	J	`jnl`	Center-Outward q-Dominance: A Sample-Computable Proxy for Strong Stochastic Dominance in Multi-Objective Optimisation. CoRR Robin van der Laag, Hao Wang, Thomas Bäck, Yingjie Fan
2025	A	`conf`	Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. GECCO Shuaiqun Pan, Yash J. Patel, Aneta Neumann, Frank Neumann, Thomas Bäck, Hao Wang
2025	J	`jnl`	Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. CoRR Shuaiqun Pan, Yash J. Patel, Aneta Neumann, Frank Neumann, Thomas Bäck, Hao Wang
2025	—	`conf`	Hot Off the Press: A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms. GECCO Companion Hao Wang, Angel E. Rodriguez-Fernandez, Lourdes Uribe, André H. Deutz, Oziel Cortés-Piña, Oliver Schütze
2025	J	`jnl`	MMD-Newton Method for Multi-objective Optimization. CoRR Hao Wang, Chenyu Shi, Angel E. Rodriguez-Fernandez, Oliver Schütze
2025	B	`conf`	Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks. CEC Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang
2025	J	`jnl`	Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks. CoRR Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang
2025	—	`conf`	Transfer Learning of Surrogate Models: Integrating Domain Warping and Affine Transformations. GECCO Companion Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang
2025	J	`jnl`	Transfer Learning of Surrogate Models: Integrating Domain Warping and Affine Transformations. CoRR Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang
2024	J	`jnl`	A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms. CoRR Hao Wang, Angel E. Rodriguez-Fernandez, Lourdes Uribe, André H. Deutz, Oziel Cortés-Piña, Oliver Schütze
2024	—	`conf`	Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis. CAI Jiajie Fan, Laure Vuaille, Thomas Bäck, Hao Wang
2024	—	`conf`	Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder. ECCV (78) Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang
2024	J	`jnl`	Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder. CoRR Jiajie Fan, Amal Trigui, Thomas Bäck, Hao Wang
2024	J	`jnl`	IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. Evol. Comput. Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2024	A	`conf`	Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. GECCO Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck
2024	J	`jnl`	Large-scale Benchmarking of Metaphor-based Optimization Heuristics. CoRR Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck
2024	J	`jnl`	Large-scale photonic computing with nonlinear disordered media. Nat. Comput. Sci. Hao Wang, Jianqi Hu, Andrea Morandi, Alfonso Nardi, Fei Xia, Xuanchen Li, Romolo Savo, Qiang Liu, Rachel Grange, Sylvain Gigan
2024	J	`jnl`	NeuroNURBS: Learning Efficient Surface Representations for 3D Solids. CoRR Jiajie Fan, Babak Gholami, Thomas Bäck, Hao Wang
2024	J	`jnl`	Optical next generation reservoir computing. CoRR Hao Wang, Jianqi Hu, YoonSeok Baek, Kohei Tsuchiyama, Malo Joly, Qiang Liu, Sylvain Gigan
2024	A*	`conf`	Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. ICML Hao Wang, Kaifeng Yang, Michael Affenzeller
2024	A	`conf`	Transfer Learning of Surrogate Models via Domain Affine Transformation. GECCO Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang
2023	J	`jnl`	Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis. CoRR Jiajie Fan, Laure Vuaille, Hao Wang, Thomas Bäck
2023	Misc	`conf`	Application of quantum-inspired generative models to small molecular datasets. QCE Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko
2023	J	`jnl`	Application of quantum-inspired generative models to small molecular datasets. CoRR Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko
2023	—	`ch.`	Bayesian Optimization. Many-Criteria Optimization and Decision Analysis Hao Wang, Kaifeng Yang
2023	Misc	`conf`	Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry. QCE Waheeda Saib, Xavier Bonet-Monroig, Vedran Dunjko, Ivano Tavernelli, Thomas Bäck, Hao Wang
2023	B	`conf`	Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CEC Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck
2023	J	`jnl`	Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CoRR Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck
2023	—	`conf`	Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye
2023	J	`jnl`	Classification-based process parameter recommendation in sheet metal forming. J. Ind. Inf. Integr. Zhengtian Ai, Ingo Heinle, Christian Schelske, Hao Wang, Peter Krause, Thomas Bäck
2023	J	`jnl`	Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. Evol. Comput. 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
2023	C	`ed.`	Evolutionary Multi-Criterion Optimization - 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20-24, 2023, Proceedings EMO Michael Emmerich, André H. Deutz, Hao Wang, Anna V. Kononova, Boris Naujoks, Ke Li, Kaisa Miettinen, Iryna Yevseyeva
2023	J	`jnl`	Large-scale photonic computing with nonlinear disordered media. CoRR Hao Wang, Jianqi Hu, Andrea Morandi, Alfonso Nardi, Fei Xia, Xuanchen Li, Romolo Savo, Qiang Liu, Rachel Grange, Sylvain Gigan
2023	J	`jnl`	On the Noise Scheduling for Generating Plausible Designs with Diffusion Models. CoRR Jiajie Fan, Laure Vuaille, Thomas Bäck, Hao Wang
2023	C	`conf`	The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. EMO André H. Deutz, Michael Emmerich, Hao Wang
2023	—	`conf`	To Switch or Not to Switch: Predicting the Benefit of Switching Between Algorithms Based on Trajectory Features. EvoApplications@EvoStar Diederick Vermetten, Hao Wang, Kevin Sim, Emma Hart
2023	J	`jnl`	To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features. CoRR Diederick Vermetten, Hao Wang, Kevin Sim, Emma Hart
2022	—	`conf`	A Systematic Approach to Analyze the Computational Cost of Robustness in Model-Assisted Robust Optimization. PPSN (1) Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
2022	J	`jnl`	Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms. CoRR Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck
2022	A	`conf`	Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. GECCO Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck
2022	J	`jnl`	Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. IEEE Trans. Evol. Comput. Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
2022	—	`conf`	Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. GECCO Companion Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
2022	—	`conf`	Benchmarking and analyzing iterative optimization heuristics with IOH profiler. GECCO Companion Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye
2022	J	`jnl`	Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points. CoRR Dominik Schröder, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2022	—	`conf`	High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. PPSN (1) Kirill A. Antonov, Elena Raponi, Hao Wang, Carola Doerr
2022	J	`jnl`	High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. CoRR Kirill A. Antonov, Elena Raponi, Hao Wang, Carola Doerr
2022	J	`jnl`	IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics. ACM Trans. Evol. Learn. Optim. Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
2022	—	`conf`	IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. GECCO Companion Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
2022	—	`conf`	Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. PPSN (1) Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr
2022	J	`jnl`	Per-run Algorithm Selection with Warm-starting using Trajectory-based Features. CoRR Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr
2022	J	`jnl`	Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. CoRR Hao Wang, Kaifeng Yang, Michael Affenzeller, Michael Emmerich
2022	J	`jnl`	The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. CoRR André H. Deutz, Michael T. M. Emmerich, Hao Wang
2021	—	`conf`	A new acquisition function for robust Bayesian optimization of unconstrained problems. GECCO Companion Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
2021	J	`jnl`	Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. CoRR Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
2021	J	`jnl`	Bayesian neural architecture search using a training-free performance metric. Appl. Soft Comput. Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck
2021	J	`jnl`	Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. CoRR Jacob de Nobel, Hao Wang, Thomas Bäck
2021	A	`conf`	Explorative data analysis of time series based algorithm features of CMA-ES variants. GECCO Jacob de Nobel, Hao Wang, Thomas Bäck
2021	J	`jnl`	IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. CoRR Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2021	B	`conf`	Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems. DSAA Duc Anh Nguyen, Jiawen Kong, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Anna V. Kononova, Thomas Bäck
2021	J	`jnl`	Is there Anisotropy in Structural Bias? CoRR Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
2021	—	`conf`	Is there anisotropy in structural bias? GECCO Companion Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
2021	C	`conf`	On Statistical Analysis of MOEAs with Multiple Performance Indicators. EMO Hao Wang, Carlos Ignacio Hernández Castellanos, Tome Eftimov
2021	J	`jnl`	Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Comput. Oper. Res. Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich
2021	J	`jnl`	Quantifying the Impact of Boundary Constraint Handling Methods on Differential Evolution. CoRR Rick Boks, Anna V. Kononova, Hao Wang
2021	—	`conf`	Quantifying the impact of boundary constraint handling methods on differential evolution. GECCO Companion Rick Boks, Anna V. Kononova, Hao Wang
2021	B	`conf`	Tabu-Driven Quantum Neighborhood Samplers. EvoCOP Charles Moussa, Hao Wang, Henri Calandra, Thomas Bäck, Vedran Dunjko
2021	J	`jnl`	Temporal convolutional autoencoder for unsupervised anomaly detection in time series. Appl. Soft Comput. Markus Thill, Wolfgang Konen, Hao Wang, Thomas Bäck
2021	J	`jnl`	Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules. CoRR Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2021	—	`conf`	Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. GECCO Companion Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2020	C	`conf`	A Classification-based Solution For Recommending Process Parameters of Production Processes Without Quality Measures. ISM Zhengtian Ai, Ingo Heinle, Christian Schelske, Hao Wang, Peter Krause, Thomas Bäck
2020	J	`jnl`	A Modular Hybridization of Particle Swarm Optimization and Differential Evolution. CoRR Rick Boks, Hao Wang, Thomas Bäck
2020	—	`conf`	A modular hybridization of particle swarm optimization and differential evolution. GECCO Companion Rick Boks, Hao Wang, Thomas Bäck
2020	—	`conf`	Automated Machine Learning for the Classification of Normal and Abnormal Electromyography Data. IEEE BigData Marios Kefalas, Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck
2020	J	`jnl`	Bayesian Neural Architecture Search using A Training-Free Performance Metric. CoRR Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck
2020	J	`jnl`	Benchmarking a $(μ+λ)$ Genetic Algorithm with Configurable Crossover Probability. CoRR Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck
2020	—	`conf`	Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. PPSN (2) Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck
2020	—	`conf`	Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion Hao Wang, Carola Doerr, Ofer M. Shir, Thomas Bäck
2020	J	`jnl`	Benchmarking discrete optimization heuristics with IOHprofiler. Appl. Soft Comput. Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
2020	—	`conf`	Can Compact Optimisation Algorithms Be Structurally Biased? PPSN (1) Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
2020	B	`conf`	Can Single Solution Optimisation Methods Be Structurally Biased? CEC Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck
2020	J	`jnl`	Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck
2020	B	`conf`	Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models. IJCNN Ullah Ullah, Zhao Xu, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
2020	—	`conf`	Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization. SSCI Sibghat Ullah, Duc Anh Nguyen, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
2020	—	`conf`	High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. PPSN (1) Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr
2020	J	`jnl`	High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. CoRR Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr
2020	J	`jnl`	IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
2020	A	`conf`	Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. GECCO Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2020	—	`conf`	Neural Network Design: Learning from Neural Architecture Search. SSCI Bas van Stein, Hao Wang, Thomas Bäck
2020	J	`jnl`	Neural Network Design: Learning from Neural Architecture Search. CoRR Bas van Stein, Hao Wang, Thomas Bäck
2020	J	`jnl`	On Statistical Analysis of MOEAs with Multiple Performance Indicators. CoRR Hao Wang, Carlos Ignacio Hernández Castellanos, Tome Eftimov
2020	—	`ed.`	Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I PPSN (1) Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann
2020	—	`ed.`	Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II PPSN (2) Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann
2020	—	`conf`	Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. SSCI Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke
2020	J	`jnl`	Squirrel: A Switching Hyperparameter Optimizer. CoRR 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
2020	J	`jnl`	The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. IEEE Trans. Cybern. Víctor Adrián Sosa-Hernández, Oliver Schütze, Hao Wang, André H. Deutz, Michael Emmerich
2020	C	`conf`	Towards Data-driven Services in Vehicles. VEHITS Milan Koch, Hao Wang, Robert Bürgel, Thomas Bäck
2020	J	`jnl`	Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case. CoRR Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2020	A	`conf`	Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. GECCO Diederick Vermetten, Hao Wang, Thomas Bäck, Carola Doerr
2019	—	`conf`	An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. SSCI Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck
2019	A*	`conf`	Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. ICDM Sina Däubener, Sebastian Schmitt, Hao Wang, Peter Krause, Thomas Bäck
2019	—	`conf`	Automated Machine Learning for EEG-Based Classification of Parkinson's Disease Patients. IEEE BigData Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck
2019	B	`conf`	Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. IJCNN Bas van Stein, Hao Wang, Thomas Bäck
2019	—	`conf`	Bayesian performance analysis for black-box optimization benchmarking. GECCO (Companion) Borja Calvo, Ofer M. Shir, Josu Ceberio, Carola Doerr, Hao Wang, Thomas Bäck, José Antonio Lozano
2019	J	`jnl`	Benchmarking Discrete Optimization Heuristics with IOHprofiler. CoRR Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
2019	—	`conf`	Benchmarking discrete optimization heuristics with IOHprofiler. GECCO (Companion) Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
2019	B	`conf`	Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution. CEC Hao Wang, Yitan Lou, Thomas Bäck
2019	J	`jnl`	Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies. Evol. Comput. Hao Wang, Michael Emmerich, Thomas Bäck
2019	—	`conf`	On the potential of evolution strategies for neural network weight optimization. GECCO (Companion) Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss
2019	J	`jnl`	Search Dynamics on Multimodal Multiobjective Problems. Evol. Comput. Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich
2019	J	`jnl`	Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. CoRR Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
2019	—	`conf`	Switching Between Swarm Optimization Algorithms During a Run: An Empirical Study. SSCI Teddy Etoeharnowo, Koen Castelein, Hao Wang, Thomas Bäck
2018	—	`conf`	A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck
2018	J	`jnl`	Automatic Configuration of Deep Neural Networks with EGO. CoRR Bas van Stein, Hao Wang, Thomas Bäck
2018	B	`conf`	Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. CEC Hao Wang, Michael Emmerich, Thomas Bäck
2018	—	`ch.`	Evolution Strategies. Handbook of Heuristics Michael Emmerich, Ofer M. Shir, Hao Wang
2018	J	`jnl`	IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. CoRR Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck
2018	—	`conf`	Machine Learning for Predicting the Damaged Parts of a Low Speed Vehicle Crash. ICDIM Milan Koch, Hao Wang, Thomas Bäck
2018	—	`conf`	Ranking empirical cumulative distribution functions using stochastic and pareto dominance. GECCO (Companion) Hao Wang, Thomas Bäck
2018	J	`jnl`	Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling (1+λ) EA Variants on OneMax and LeadingOnes. CoRR Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck
2018	A	`conf`	Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. GECCO Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck
2017	B	`conf`	A new acquisition function for Bayesian optimization based on the moment-generating function. SMC Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck
2017	A	`conf`	Algorithm configuration data mining for CMA evolution strategies. GECCO Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck
2017	—	`conf`	Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning. QTOP@NetSys Sheir Yarkoni, Hao Wang, Aske Plaat, Thomas Bäck
2017	J	`jnl`	Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck
2017	C	`conf`	Hypervolume Indicator Gradient Ascent Multi-objective Optimization. EMO Hao Wang, André H. Deutz, Thomas Bäck, Michael Emmerich
2017	A	`conf`	Time complexity reduction in efficient global optimization using cluster kriging. GECCO Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck
2016	—	`ch.`	A Multicriteria Generalization of Bayesian Global Optimization. Advances in Stochastic and Deterministic Global Optimization Michael Emmerich, Kaifeng Yang, André H. Deutz, Hao Wang, Carlos M. Fonseca
2016	B	`conf`	Balancing risk and expected gain in kriging-based global optimization. CEC Hao Wang, Michael T. M. Emmerich, Thomas Bäck
2016	J	`jnl`	Evolving the Structure of Evolution Strategies. CoRR Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck
2016	—	`conf`	Evolving the structure of Evolution Strategies. SSCI Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck
2016	B	`conf`	Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck
2016	—	`conf`	SMS-EMOA with multiple dynamic reference points. ICNC-FSKD Zhiwei Yang, Hao Wang, Kaifeng Yang, Thomas Bäck, Michael Emmerich
2016	A	`conf`	Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich
2015	—	`conf`	Multi-point Efficient Global Optimization Using Niching Evolution Strategy. EVOLVE Hao Wang, Thomas Bäck, Michael T. M. Emmerich
2015	—	`conf`	On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. NEO Hao Wang, Yiyi Ren, André H. Deutz, Michael T. M. Emmerich
2015	B	`conf`	Optimally Weighted Cluster Kriging for Big Data Regression. IDA Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich
2014	Misc	`conf`	Mirrored orthogonal sampling with pairwise selection in evolution strategies. SAC Hao Wang, Michael Emmerich, Thomas Bäck