Power Distribution Network Reconfiguration by Evolutionary Integer Programming. - Kaifeng Yang; Michael T. M. Emmerich; Rui Li 001; Ji Wang; Thomas Bäck (PPSN, 2014)

Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant. - Kaifeng Yang; Daniel Gaida; Thomas Bäck; Michael Emmerich 001 (CEC, 2015)

Faster Exact Algorithms for Computing Expected Hypervolume Improvement. - Iris Hupkens; André H. Deutz; Kaifeng Yang; Michael T. M. Emmerich (EMO (2), 2015)

A Multicriteria Generalization of Bayesian Global Optimization. - Michael Emmerich 001; Kaifeng Yang; André H. Deutz; Hao Wang 025; Carlos M. Fonseca (Advances in Stochastic and Deterministic Global Optimization, 2016)

Truncated expected hypervolume improvement: Exact computation and application. - Kaifeng Yang; André H. Deutz; Zhiwei Yang 002; Thomas Bäck; Michael T. M. Emmerich (CEC, 2016)

Preference-based multiobjective optimization using truncated expected hypervolume improvement. - Kaifeng Yang; Longmei Li; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (ICNC-FSKD, 2016)

SMS-EMOA with multiple dynamic reference points. - Zhiwei Yang 002; Hao Wang 025; Kaifeng Yang; Thomas Bäck; Michael Emmerich 001 (ICNC-FSKD, 2016)

A new approach to target region based multiobjective evolutionary algorithms. - Yali Wang 002; Longmei Li; Kaifeng Yang; Michael T. M. Emmerich (CEC, 2017)

Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time. - Kaifeng Yang; Michael Emmerich 001; André H. Deutz; Carlos M. Fonseca (EMO, 2017)

Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement. - Pramudita Satria Palar; Kaifeng Yang; Koji Shimoyama; Michael Emmerich 001; Thomas Bäck (GECCO, 2018)

The Expected R2-Indicator Improvement for Multi-objective Bayesian Optimization. - André H. Deutz; Michael Emmerich 001; Kaifeng Yang (EMO, 2019)

A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization. - Kaifeng Yang; Pramudita Satria Palar; Michael Emmerich 001; Koji Shimoyama; Thomas Bäck (GECCO, 2019)

Efficient computation of expected hypervolume improvement using box decomposition algorithms. - Kaifeng Yang; Michael Emmerich 001; André H. Deutz; Thomas Bäck (J. Glob. Optim., 2019)

Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient. - Kaifeng Yang; Michael Emmerich 001; André H. Deutz; Thomas Bäck (Swarm Evol. Comput., 2019)

Infill Criteria for Multiobjective Bayesian Optimization. - Michael T. M. Emmerich; Kaifeng Yang; André H. Deutz (High-Performance Simulation-Based Optimization, 2020)

Quantifying Uncertainties of Residuals in Symbolic Regression via Kriging. - Kaifeng Yang; Michael Affenzeller (ISM, 2021)

Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way. - Michael Affenzeller; Michael Bögl; Lukas Fischer 001; Florian Sobieczky; Kaifeng Yang; Jan Zenisek (SYNASC, 2022)

Wheat head counting in the wild by an augmented feature pyramid networks-based convolutional neural network. - Jun Sun 019; Kaifeng Yang; Chen Chen; Jifeng Shen; Yu Yang; Xiaohong Wu; Tomas Norton (Comput. Electron. Agric., 2022)

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. - Hao Wang 025; Kaifeng Yang; Michael Affenzeller; Michael Emmerich 001 (CoRR, 2022)

Beet seedling and weed recognition based on convolutional neural network and multi-modality images. - Jun Sun 019; Kaifeng Yang; Xiaofei He 003; Yuanqiu Luo; Xiaohong Wu; Jifeng Shen (Multim. Tools Appl., 2022)

A parallel technique for multi-objective Bayesian global optimization: Using a batch selection of probability of improvement. - Kaifeng Yang; Michael Affenzeller; Guozhi Dong (Swarm Evol. Comput., 2022)

Surface Defect Detection of Heat Sink Based on Lightweight Fully Convolutional Network. - Kaifeng Yang; Yuliang Liu; Shiwen Zhang 001; Jiajian Cao (IEEE Trans. Instrum. Meas., 2022)

Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression. - Kaifeng Yang; Michael Affenzeller (EMO, 2023)

Walking through the Quadratic Assignment-Instance Space: Algorithm Performance and Landscape Measures. - Bernhard Werth; Johannes Karder; Andreas Beham; Erik Pitzer; Kaifeng Yang; Stefan Wagner 002 (GECCO Companion, 2023)

A New Acquisition Function for Multi-objective Bayesian Optimization: Correlated Probability of Improvement. - Kaifeng Yang; Kai Chen; Michael Affenzeller; Bernhard Werth (GECCO Companion, 2023)

Gradients of Acquisition Functions for Bi-objective Bayesian optimization. - Kaifeng Yang; Sixuan Liu; Michael Affenzeller; Guozhi Dong (ICNC-FSKD, 2023)

Challenges of ELA-Guided Function Evolution Using Genetic Programming. - Fu Xing Long; Diederick Vermetten; Anna V. Kononova; Roman Kalkreuth; Kaifeng Yang; Thomas Bäck; Niki van Stein (IJCCI, 2023)

Segmentation and recognition of filed sweet pepper based on improved self-attention convolutional neural networks. - Weidong Zhu; Jun Sun 019; Simin Wang; Kaifeng Yang; Jifeng Shen; Xin Zhou (Multim. Syst., 2023)

Bayesian Optimization. - Hao Wang 025; Kaifeng Yang (Many-Criteria Optimization and Decision Analysis, 2023)

Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files. - Fu Xing Long; Diederick Vermetten; Anna V. Kononova; Roman Kalkreuth; Kaifeng Yang; Thomas Bäck; Niki van Stein (Zenodo, 2023)

Age-Layer-Population-Structure with Self-adaptation in Optimization. - Kaifeng Yang; Bernhard Werth; Michael Affenzeller (EUROCAST (3), 2024)

A Functional Analysis Approach to Symbolic Regression. - Kirill Antonov; Roman Kalkreuth; Kaifeng Yang; Thomas Bäck; Niki van Stein; Anna V. Kononova (GECCO, 2024)

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. - Hao Wang 025; Kaifeng Yang; Michael Affenzeller (ICML, 2024)

Realistic Pulse Waveforms Estimation via Contrastive Learning in Remote Photoplethysmography. - Bowei Dong; Yuliang Liu; Kaifeng Yang; Jiajian Cao (IEEE Trans. Instrum. Meas., 2024)

Population diversity and inheritance in genetic programming for symbolic regression. - Bogdan Burlacu; Kaifeng Yang; Michael Affenzeller (Nat. Comput., 2024)

Efficient Federated Bayesian Optimization with Symbolic Regression Model. - Xilu Wang 001; Kaifeng Yang; Peng Liao; Mengxuan Zhang 003; Yaochu Jin (CEC, 2025)