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Ke Tang 0001
Person information
- affiliation: Southern University of Science and Technology, Shenzhen China
- affiliation (former): University of Science and Technology of China, School of Computer Science and Technology, China
- affiliation (former): Nanyang Technological University, Singapore
Other persons with the same name
- Ke Tang — disambiguation page
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Journal Articles
- 2025
- [j132]Dan-Xuan Liu
, Yu-Ran Gu
Migrant Resettlement by Evolutionary Multiobjective Optimization. IEEE Trans. Artif. Intell. 6(1): 51-65 (2025) - [j131]Pinhan Fu, Xinyan Liang
Multi-Scale Features Are Effective for Multi-Modal Classification: An Architecture Search Viewpoint. IEEE Trans. Circuits Syst. Video Technol. 35(2): 1070-1083 (2025) - [j130]Bingdong Li
Causal Inference-Based Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 29(2): 444-458 (2025) - [j129]Shenglian Tan
A Surrogate-Assisted Evolutionary Framework for Expensive Multitask Optimization Problems. IEEE Trans. Evol. Comput. 29(3): 779-793 (2025) - [j128]Jiahao Wu
Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation. IEEE Trans. Knowl. Data Eng. 37(1): 162-173 (2025) - [j127]Tianyu Zhang
Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs. IEEE Trans. Neural Networks Learn. Syst. 36(3): 4462-4476 (2025) - 2024
- [j126]Xuanfeng Li
Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. IEEE Trans. Cybern. 54(12): 7969-7980 (2024) - [j125]Yayu Zhang, Yuhua Qian
ESSR: Evolving Sparse Sharing Representation for Multitask Learning. IEEE Trans. Evol. Comput. 28(3): 748-762 (2024) - [j124]Tong Guo
A Knee-Guided Evolutionary Algorithm for Multi-Objective Air Traffic Flow Management. IEEE Trans. Evol. Comput. 28(4): 994-1008 (2024) - [j123]Tong Guo
Cooperative Co-Evolution for Large-Scale Multiobjective Air Traffic Flow Management. IEEE Trans. Evol. Comput. 28(6): 1644-1658 (2024) - [j122]Shengcai Liu
Effective and Imperceptible Adversarial Textual Attack Via Multi-objectivization. ACM Trans. Evol. Learn. Optim. 4(3): 16:1-16:23 (2024) - [j121]Ning Lu, Shengcai Liu, Rui He, Yew-Soon Ong, Qi Wang, Ke Tang:
Large Language Models can be Guided to Evade AI-generated Text Detection. Trans. Mach. Learn. Res. 2024 (2024) - [j120]Guiying Li
Stage-Wise Magnitude-Based Pruning for Recurrent Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(2): 1666-1680 (2024) - [j119]Zhiyao Zhang
A Two-Phase Kriging-Assisted Evolutionary Algorithm for Expensive Constrained Multiobjective Optimization Problems. IEEE Trans. Syst. Man Cybern. Syst. 54(8): 4579-4591 (2024) - [j118]Ming Chen, Yonghao Du, Ke Tang, Lining Xing
Learning to Construct a Solution for the Agile Satellite Scheduling Problem With Time-Dependent Transition Times. IEEE Trans. Syst. Man Cybern. Syst. 54(10): 5949-5963 (2024) - 2023
- [j117]Shengcai Liu
How Good is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem. IEEE Comput. Intell. Mag. 18(3): 14-28 (2023) - [j116]Biyue Li
A multi-objective memetic algorithm with adaptive local search for airspace complexity mitigation. Swarm Evol. Comput. 83: 101400 (2023) - [j115]Wenjie Chen
Multi-Fidelity Simulation Modeling for Discrete Event Simulation: An Optimization Perspective. IEEE Trans Autom. Sci. Eng. 20(2): 1156-1169 (2023) - [j114]Chao Qian, Dan-Xuan Liu, Chao Feng, Ke Tang:
Multi-objective evolutionary algorithms are generally good: Maximizing monotone submodular functions over sequences. Theor. Comput. Sci. 943: 241-266 (2023) - [j113]Peilan Xu, Wenjian Luo
Difficulty and Contribution-Based Cooperative Coevolution for Large-Scale Optimization. IEEE Trans. Evol. Comput. 27(5): 1355-1369 (2023) - [j112]Rui He
Multi-Domain Active Learning: Literature Review and Comparative Study. IEEE Trans. Emerg. Top. Comput. Intell. 7(3): 791-804 (2023) - [j111]Zhenwei Zhang
Fast Multi-Grid Methods for Minimizing Curvature Energies. IEEE Trans. Image Process. 32: 1716-1731 (2023) - [j110]Zeyu Dai
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. ACM Trans. Intell. Syst. Technol. 14(3): 45:1-45:20 (2023) - 2022
- [j109]Hongze Wang, Xuerong Li, Wenjing Hong, Ke Tang:
Multi-objective approaches to portfolio optimization with market impact costs. Memetic Comput. 14(4): 411-421 (2022) - [j108]Peng Yang
Evolutionary reinforcement learning via cooperative coevolutionary negatively correlated search. Swarm Evol. Comput. 68: 100974 (2022) - [j107]Shengcai Liu
Efficient Combinatorial Optimization for Word-Level Adversarial Textual Attack. IEEE ACM Trans. Audio Speech Lang. Process. 30: 98-111 (2022) - [j106]Shengcai Liu
Generative Adversarial Construction of Parallel Portfolios. IEEE Trans. Cybern. 52(2): 784-795 (2022) - [j105]Tao Sun
Gradient Descent Learning With Floats. IEEE Trans. Cybern. 52(3): 1763-1771 (2022) - [j104]Zhi-Zhong Liu
Handling Constrained Multiobjective Optimization Problems via Bidirectional Coevolution. IEEE Trans. Cybern. 52(10): 10163-10176 (2022) - [j103]Xiaofen Lu
Dynamic Optimization in Fast-Changing Environments via Offline Evolutionary Search. IEEE Trans. Evol. Comput. 26(3): 431-445 (2022) - [j102]Liang Feng
Towards Faster Vehicle Routing by Transferring Knowledge From Customer Representation. IEEE Trans. Intell. Transp. Syst. 23(2): 952-965 (2022) - [j101]Biyue Li
A Deep Unsupervised Learning Approach for Airspace Complexity Evaluation. IEEE Trans. Intell. Transp. Syst. 23(8): 11739-11751 (2022) - [j100]Chengbin Hou
GloDyNE: Global Topology Preserving Dynamic Network Embedding. IEEE Trans. Knowl. Data Eng. 34(10): 4826-4837 (2022) - 2021
- [j99]Chao Qian
Analysis of Noisy Evolutionary Optimization When Sampling Fails. Algorithmica 83(4): 940-975 (2021) - [j98]Chao Bian, Chao Qian, Yang Yu, Ke Tang:
On the robustness of median sampling in noisy evolutionary optimization. Sci. China Inf. Sci. 64(5) (2021) - [j97]Jialin Liu
Robust Optimization in Uncertain Capacitated Arc Routing Problems: Progresses and Perspectives [Review Article]. IEEE Comput. Intell. Mag. 16(1): 63-82 (2021) - [j96]Peng Yang, Qi Yang
Parallel exploration via negatively correlated search. Frontiers Comput. Sci. 15(5): 155333 (2021) - [j95]Wenjing Hong
Evolutionary Computation for Large-scale Multi-objective Optimization: A Decade of Progresses. Int. J. Autom. Comput. 18(2): 155-169 (2021) - [j94]Yunwen Lei, Ting Hu, Ke Tang:
Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions. J. Mach. Learn. Res. 22: 25:1-25:41 (2021) - [j93]Minshi Chen, Jianxun Chen, Peng Yang, Shengcai Liu, Ke Tang:
A heuristic repair method for dial-a-ride problem in intracity logistic based on neighborhood shrinking. Multim. Tools Appl. 80(20): 30775-30787 (2021) - [j92]Yunwen Lei
Learning Rates for Stochastic Gradient Descent With Nonconvex Objectives. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4505-4511 (2021) - [j91]Zeyu Dai
An optima-identified framework with brain storm optimization for multimodal optimization problems. Swarm Evol. Comput. 62: 100827 (2021) - [j90]Shengcai Liu
Memetic search for vehicle routing with simultaneous pickup-delivery and time windows. Swarm Evol. Comput. 66: 100927 (2021) - [j89]Liang Feng
Explicit Evolutionary Multitasking for Combinatorial Optimization: A Case Study on Capacitated Vehicle Routing Problem. IEEE Trans. Cybern. 51(6): 3143-3156 (2021) - [j88]Wenjing Hong
Efficient Minimum Cost Seed Selection With Theoretical Guarantees for Competitive Influence Maximization. IEEE Trans. Cybern. 51(12): 6091-6104 (2021) - [j87]Ke Tang
Few-Shots Parallel Algorithm Portfolio Construction via Co-Evolution. IEEE Trans. Evol. Comput. 25(3): 595-607 (2021) - [j86]Bo Yuan
Cooperative Coevolution-based Design Space Exploration for Multi-mode Dataflow Mapping. ACM Trans. Embed. Comput. Syst. 20(3): 21:1-21:25 (2021) - [j85]Yu Zhang
A Survey on Neural Network Interpretability. IEEE Trans. Emerg. Top. Comput. Intell. 5(5): 726-742 (2021) - 2020
- [j84]Ning Shi, Zexuan Zhu, Ke Tang, David Parker
ATEN: And/Or tree ensemble for inferring accurate Boolean network topology and dynamics. Bioinform. 36(2): 578-585 (2020) - [j83]Chengbin Hou
RoSANE: Robust and scalable attributed network embedding for sparse networks. Neurocomputing 409: 231-243 (2020) - [j82]Dongbin Jiao
Optimal Energy-Delay Scheduling for Energy-Harvesting WSNs With Interference Channel via Negatively Correlated Search. IEEE Internet Things J. 7(3): 1690-1703 (2020) - [j81]Chao Bian, Chao Qian, Ke Tang, Yang Yu:
Running time analysis of the (1+1)-EA for robust linear optimization. Theor. Comput. Sci. 843: 57-72 (2020) - [j80]Feng Wang, Yixuan Li, Aimin Zhou
An Estimation of Distribution Algorithm for Mixed-Variable Newsvendor Problems. IEEE Trans. Evol. Comput. 24(3): 479-493 (2020) - [j79]Wenbo Du
Network-Based Heterogeneous Particle Swarm Optimization and Its Application in UAV Communication Coverage. IEEE Trans. Emerg. Top. Comput. Intell. 4(3): 312-323 (2020) - [j78]Yunwen Lei
Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient Assumptions. IEEE Trans. Neural Networks Learn. Syst. 31(10): 4394-4400 (2020) - [j77]Di Wu
Particle Swarm Optimization with Moving Particles on Scale-Free Networks. IEEE Trans. Netw. Sci. Eng. 7(1): 497-506 (2020) - 2019
- [j76]Peng Yang
A Parallel Divide-and-Conquer-Based Evolutionary Algorithm for Large-Scale Optimization. IEEE Access 7: 163105-163118 (2019) - [j75]Chao Qian, Yang Yu, Ke Tang, Xin Yao, Zhi-Hua Zhou:
Maximizing submodular or monotone approximately submodular functions by multi-objective evolutionary algorithms. Artif. Intell. 275: 279-294 (2019) - [j74]Chao Qian, Chao Bian, Wu Jiang, Ke Tang:
Running Time Analysis of the ( $$1+1$$ 1 + 1 )-EA for OneMax and LeadingOnes Under Bit-Wise Noise. Algorithmica 81(2): 749-795 (2019) - [j73]José Antonio Lozano, Ke Tang, Xin Yao
Preface. Nat. Comput. 18(2): 285-286 (2019) - [j72]Xiaofen Lu
Evolutionary optimization with hierarchical surrogates. Swarm Evol. Comput. 47: 21-32 (2019) - [j71]Zhi-Zhong Liu
An Adaptive Framework to Tune the Coordinate Systems in Nature-Inspired Optimization Algorithms. IEEE Trans. Cybern. 49(4): 1403-1416 (2019) - [j70]Xiaoliang Ma, Xiaodong Li
A Survey on Cooperative Co-Evolutionary Algorithms. IEEE Trans. Evol. Comput. 23(3): 421-441 (2019) - [j69]Wenjing Hong, Ke Tang, Aimin Zhou, Hisao Ishibuchi
A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 23(3): 525-537 (2019) - [j68]Xinle Liang
QoS-Aware Web Service Selection with Internal Complementarity. IEEE Trans. Serv. Comput. 12(2): 276-289 (2019) - 2018
- [j67]Wenbo Du, Mingyuan Zhang, Wen Ying, Matjaz Perc
The networked evolutionary algorithm: A network science perspective. Appl. Math. Comput. 338: 33-43 (2018) - [j66]Thomas Weise, Xiaofeng Wang, Qi Qi, Bin Li, Ke Tang:
Automatically discovering clusters of algorithm and problem instance behaviors as well as their causes from experimental data, algorithm setups, and instance features. Appl. Soft Comput. 73: 366-382 (2018) - [j65]Chao Qian, Yang Yu, Ke Tang, Yaochu Jin
On the Effectiveness of Sampling for Evolutionary Optimization in Noisy Environments. Evol. Comput. 26(2) (2018) - [j64]Jinyuan Zhang, Aimin Zhou
Preselection via classification: A case study on evolutionary multiobjective optimization. Inf. Sci. 465: 388-403 (2018) - [j63]Peng Yang
Turning High-Dimensional Optimization Into Computationally Expensive Optimization. IEEE Trans. Evol. Comput. 22(1): 143-156 (2018) - [j62]Xiaofen Lu
Cooperative Co-Evolution-Based Design Optimization: A Concurrent Engineering Perspective. IEEE Trans. Evol. Comput. 22(2): 173-188 (2018) - [j61]Chao Qian
Constrained Monotone k-Submodular Function Maximization Using Multiobjective Evolutionary Algorithms With Theoretical Guarantee. IEEE Trans. Evol. Comput. 22(4): 595-608 (2018) - [j60]Yu Sun
Concept Drift Adaptation by Exploiting Historical Knowledge. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4822-4832 (2018) - 2017
- [j59]Yuzhou Zhang, Yi Mei
Memetic algorithm with route decomposing for periodic capacitated arc routing problem. Appl. Soft Comput. 52: 1130-1142 (2017) - [j58]He Jiang, Ke Tang, Justyna Petke
Search Based Software Engineering [Guest Editorial]. IEEE Comput. Intell. Mag. 12(2): 23-71 (2017) - [j57]Xingyi Zhang, Fuchen Duan, Lei Zhang, Fan Cheng, Yaochu Jin
Pattern Recommendation in Task-oriented Applications: A Multi-Objective Perspective [Application Notes]. IEEE Comput. Intell. Mag. 12(3): 43-53 (2017) - [j56]Jiaqi Zhao, Vitor Basto-Fernandes, Licheng Jiao
Corrigendum to 'Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms' [Information Sciences volumes 367-368 (2016) 80-104]. Inf. Sci. 403: 55 (2017) - [j55]Xiao-Peng Ji, Xian-Bin Cao, Wenbo Du, Ke Tang:
An evolutionary approach for dynamic single-runway arrival sequencing and scheduling problem. Soft Comput. 21(23): 7021-7037 (2017) - [j54]Ke Tang
A Scalable Approach to Capacitated Arc Routing Problems Based on Hierarchical Decomposition. IEEE Trans. Cybern. 47(11): 3928-3940 (2017) - [j53]Kaiquan Cai, Jun Zhang, Ming-Ming Xiao
Simultaneous Optimization of Airspace Congestion and Flight Delay in Air Traffic Network Flow Management. IEEE Trans. Intell. Transp. Syst. 18(11): 3072-3082 (2017) - [j52]Jinhong Zhong, Peng Yang
A Quality-Sensitive Method for Learning from Crowds. IEEE Trans. Knowl. Data Eng. 29(12): 2643-2654 (2017) - 2016
- [j51]Zhenyu Yang, Bernhard Sendhoff
Target shape design optimization by evolving B-splines with cooperative coevolution. Appl. Soft Comput. 48: 672-682 (2016) - [j50]Jiaqi Zhao, Vitor Basto-Fernandes
Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms. Inf. Sci. 367-368: 80-104 (2016) - [j49]Thomas Weise, Yuezhong Wu, Raymond Chiong
Global versus local search: the impact of population sizes on evolutionary algorithm performance. J. Glob. Optim. 66(3): 511-534 (2016) - [j48]Ke Tang, Peng Yang
Negatively Correlated Search. IEEE J. Sel. Areas Commun. 34(3): 542-550 (2016) - [j47]Wenjing Hong, Ke Tang:
Convex hull-based multi-objective evolutionary computation for maximizing receiver operating characteristics performance. Memetic Comput. 8(1): 35-44 (2016) - [j46]Xiao-Peng Ji, Xianbin Cao, Ke Tang:
Sequence searching and evaluation: a unified approach for aircraft arrival sequencing and scheduling problems. Memetic Comput. 8(2): 109-123 (2016) - [j45]Juan Wang, Ke Tang, José Antonio Lozano, Xin Yao
Estimation of the Distribution Algorithm With a Stochastic Local Search for Uncertain Capacitated Arc Routing Problems. IEEE Trans. Evol. Comput. 20(1): 96-109 (2016) - [j44]Shan He
Cooperative Co-Evolutionary Module Identification With Application to Cancer Disease Module Discovery. IEEE Trans. Evol. Comput. 20(6): 874-891 (2016) - [j43]Bingdong Li, Ke Tang
Stochastic Ranking Algorithm for Many-Objective Optimization Based on Multiple Indicators. IEEE Trans. Evol. Comput. 20(6): 924-938 (2016) - [j42]Yu Sun, Ke Tang, Leandro L. Minku
Online Ensemble Learning of Data Streams with Gradually Evolved Classes. IEEE Trans. Knowl. Data Eng. 28(6): 1532-1545 (2016) - 2015
- [j41]Bingdong Li, Jinlong Li, Ke Tang, Xin Yao
Many-Objective Evolutionary Algorithms: A Survey. ACM Comput. Surv. 48(1): 13:1-13:35 (2015) - [j40]Mohammad Nabi Omidvar
Designing benchmark problems for large-scale continuous optimization. Inf. Sci. 316: 419-436 (2015) - [j39]Xiaodong Li
Editorial for the special issue of Information Sciences Journal (ISJ) on "Nature-inspired algorithms for large scale global optimization". Inf. Sci. 316: 437-439 (2015) - [j38]Peng Yang
Improving Estimation of Distribution Algorithm on Multimodal Problems by Detecting Promising Areas. IEEE Trans. Cybern. 45(8): 1438-1449 (2015) - [j37]Lingxi Li, Ke Tang:
History-Based Topological Speciation for Multimodal Optimization. IEEE Trans. Evol. Comput. 19(1): 136-150 (2015) - [j36]Pu Wang, Michael Emmerich
Convex Hull-Based Multiobjective Genetic Programming for Maximizing Receiver Operating Characteristic Performance. IEEE Trans. Evol. Comput. 19(2): 188-200 (2015) - [j35]Haobo Fu, Bernhard Sendhoff
Robust Optimization Over Time: Problem Difficulties and Benchmark Problems. IEEE Trans. Evol. Comput. 19(5): 731-745 (2015) - [j34]Lunjun Wan, Ke Tang, Mingzhi Li, Yanfei Zhong, A. Kai Qin
Collaborative Active and Semisupervised Learning for Hyperspectral Remote Sensing Image Classification. IEEE Trans. Geosci. Remote. Sens. 53(5): 2384-2396 (2015) - [j33]Xiaoxing Yang
A Learning-to-Rank Approach to Software Defect Prediction. IEEE Trans. Reliab. 64(1): 234-246 (2015) - [j32]Peng Yang
Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints. IEEE Trans. Robotics 31(5): 1130-1146 (2015) - 2014
- [j31]Thomas Weise, Raymond Chiong
Benchmarking Optimization Algorithms: An Open Source Framework for the Traveling Salesman Problem. IEEE Comput. Intell. Mag. 9(3): 40-52 (2014) - [j30]Xiaofen Lu, Ke Tang, Bernhard Sendhoff
A review of concurrent optimisation methods. Int. J. Bio Inspired Comput. 6(1): 22-31 (2014) - [j29]Pu Wang, Ke Tang, Thomas Weise, Edward P. K. Tsang, Xin Yao
Multiobjective genetic programming for maximizing ROC performance. Neurocomputing 125: 102-118 (2014) - [j28]Xiaofen Lu, Ke Tang, Bernhard Sendhoff
A new self-adaptation scheme for differential evolution. Neurocomputing 146: 2-16 (2014) - [j27]Ke Tang, Fei Peng, Guoliang Chen, Xin Yao
Population-based Algorithm Portfolios with automated constituent algorithms selection. Inf. Sci. 279: 94-104 (2014) - [j26]Thomas Weise, Mingxu Wan, Pu Wang, Ke Tang, Alexandre Devert, Xin Yao
Frequency Fitness Assignment. IEEE Trans. Evol. Comput. 18(2): 226-243 (2014) - 2013
- [j25]Yaochu Jin
A framework for finding robust optimal solutions over time. Memetic Comput. 5(1): 3-18 (2013) - [j24]Minlong Lin, Ke Tang, Xin Yao
Dynamic Sampling Approach to Training Neural Networks for Multiclass Imbalance Classification. IEEE Trans. Neural Networks Learn. Syst. 24(4): 647-660 (2013) - 2012
- [j23]Kaiquan Cai, Jun Zhang, Chi Zhou, Xianbin Cao, Ke Tang:
Using computational intelligence for large scale air route networks design. Appl. Soft Comput. 12(9): 2790-2800 (2012) - [j22]Alexandre Devert, Thomas Weise, Ke Tang:
A Study on Scalable Representations for Evolutionary Optimization of Ground Structures. Evol. Comput. 20(3): 453-472 (2012) - [j21]Rui Wang, Ke Tang:
Feature selection for MAUC-oriented classification systems. Neurocomputing 89: 39-54 (2012) - [j20]Thomas Weise, Raymond Chiong
Evolutionary Optimization: Pitfalls and Booby Traps. J. Comput. Sci. Technol. 27(5): 907-936 (2012) - [j19]Xiaofen Lu, Ke Tang:
Classification- and Regression-Assisted Differential Evolution for Computationally Expensive Problems. J. Comput. Sci. Technol. 27(5): 1024-1034 (2012) - [j18]Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao
A large population size can be unhelpful in evolutionary algorithms. Theor. Comput. Sci. 436: 54-70 (2012) - [j17]Thomas Weise, Ke Tang:
Evolving Distributed Algorithms With Genetic Programming. IEEE Trans. Evol. Comput. 16(2): 242-265 (2012) - [j16]Zhenyu Yang, Xiaoli Li
An Efficient Evolutionary Approach to Parameter Identification in a Building Thermal Model. IEEE Trans. Syst. Man Cybern. Part C 42(6): 957-969 (2012) - 2011
- [j15]Xin Yu, Ke Tang, Xin Yao
Immigrant schemes for evolutionary algorithms in dynamic environments: Adapting the replacement rate. Sci. China Inf. Sci. 54(7): 1352-1364 (2011) - [j14]Zhenyu Yang, Ke Tang, Xin Yao
Scalability of generalized adaptive differential evolution for large-scale continuous optimization. Soft Comput. 15(11): 2141-2155 (2011) - [j13]Yi Mei
Decomposition-Based Memetic Algorithm for Multiobjective Capacitated Arc Routing Problem. IEEE Trans. Evol. Comput. 15(2): 151-165 (2011) - 2010
- [j12]Ke Tang, Kay Chen Tan, Hisao Ishibuchi
Guest editorial: Memetic Algorithms for Evolutionary Multi-Objective Optimization. Memetic Comput. 2(1): 1 (2010) - [j11]Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao
Analysis of Computational Time of Simple Estimation of Distribution Algorithms. IEEE Trans. Evol. Comput. 14(1): 1-22 (2010) - [j10]Fei Peng, Ke Tang, Guoliang Chen, Xin Yao
Population-Based Algorithm Portfolios for Numerical Optimization. IEEE Trans. Evol. Comput. 14(5): 782-800 (2010) - [j9]Zai Wang, Ke Tang, Xin Yao
Multi-Objective Approaches to Optimal Testing Resource Allocation in Modular Software Systems. IEEE Trans. Reliab. 59(3): 563-575 (2010) - [j8]Zai Wang, Ke Tang, Xin Yao
A Memetic Algorithm for Multi-Level Redundancy Allocation. IEEE Trans. Reliab. 59(4): 754-765 (2010) - 2009
- [j7]Ke Tang, Xin Yao
From nature to computing and back. Frontiers Comput. Sci. China 3(1): 1-3 (2009) - [j6]Ke Tang, Minlong Lin, Fernanda L. Minku, Xin Yao
Selective negative correlation learning approach to incremental learning. Neurocomputing 72(13-15): 2796-2805 (2009) - [j5]Xin Yu, Ke Tang, Tianshi Chen, Xin Yao
Empirical analysis of evolutionary algorithms with immigrants schemes for dynamic optimization. Memetic Comput. 1(1): 3-24 (2009) - [j4]Ke Tang, Yi Mei
Memetic Algorithm With Extended Neighborhood Search for Capacitated Arc Routing Problems. IEEE Trans. Evol. Comput. 13(5): 1151-1166 (2009) - [j3]Yi Mei
A Global Repair Operator for Capacitated Arc Routing Problem. IEEE Trans. Syst. Man Cybern. Part B 39(3): 723-734 (2009) - 2008
- [j2]Ke Tang, Xin Yao
Special Issue on "Nature Inspired Problem-Solving". Inf. Sci. 178(15): 2983-2984 (2008) - [j1]Zhenyu Yang, Ke Tang, Xin Yao
Large scale evolutionary optimization using cooperative coevolution. Inf. Sci. 178(15): 2985-2999 (2008)
Conference and Workshop Papers
- 2025
- [c126]Bingdong Li, Zixiang Di, Yongfan Lu, Hong Qian, Feng Wang, Peng Yang, Ke Tang, Aimin Zhou:
Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models. AAAI 2025: 27063-27071 - [c125]Qiaozhi Zhang, Miqing Li, Ke Tang, Xin Yao:
When Is Non-deteriorating Population Update in MOEAs Beneficial? EMO (2) 2025: 31-45 - [c124]Hong Qian, Yiyi Zhu, Xiang Shu, Shuo Liu, Yaolin Wen, Xin An, Huakang Lu, Aimin Zhou, Ke Tang, Yang Yu:
SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization. ICLR 2025 - [c123]Jiahao Wu
Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation. WWW (Companion Volume) 2025: 1402-1406 - 2024
- [c122]Wenjing Hong, Cheng Chen, Zexuan Zhu, Ke Tang:
An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design. CEC 2024: 1-8 - [c121]Shengcai Liu, Caishun Chen, Xinghua Qu, Ke Tang, Yew-Soon Ong:
Large Language Models as Evolutionary Optimizers. CEC 2024: 1-8 - [c120]Hui Ouyang, Cheng Chen, Ke Tang:
Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning. IIP (1) 2024: 63-78 - 2023
- [c119]Shengcai Liu, Fu Peng, Ke Tang:
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. AAAI 2023: 8852-8860 - [c118]Ke Tang, Xiuxiu Hu, Pingsheng Chen, Siyu Xia:
Fibrosis Grading Methods for Renal Whole Slide Images Based on Uncertainty Estimation. ACPR (2) 2023: 396-408 - [c117]Shaofeng Zhang, Shengcai Liu, Ke Tang:
A Sample Reuse Strategy for Dynamic Influence Maximization Problem. BIC-TA (2) 2023: 107-120 - [c116]Donghui Zhao, Xiaofen Lu, Ke Tang:
An Adaptive Knowledge Transfer Strategy for Evolutionary Dynamic Multi-objective Optimization. BIC-TA (1) 2023: 185-199 - [c115]Rui He
Perturbation-Based Two-Stage Multi-Domain Active Learning. CIKM 2023: 3933-3937 - [c114]Rui He
Multi-Domain Learning from Insufficient Annotations. ECAI 2023: 1028-1035 - 2022
- [c113]Lan Tang, Xiaxi Li, Jinyuan Zhang, Guiying Li, Peng Yang, Ke Tang:
Enabling Surrogate-Assisted Evolutionary Reinforcement Learning via Policy Embedding. BIC-TA 2022: 233-247 - [c112]Jiahao Wu
Disentangled Contrastive Learning for Social Recommendation. CIKM 2022: 4570-4574 - [c111]Wenjian Luo, Hongwei Zhang, Linghao Kong, Zhijian Chen, Ke Tang:
Defending Adversarial Examples by Negative Correlation Ensemble. DMBD (2) 2022: 424-438 - [c110]Chengbin Hou
GloDyNE: Global Topology Preserving Dynamic Network Embedding (Extended Abstract). ICDE 2022: 1545-1546 - [c109]Zhiyuan Wang
Zero-Shot Knowledge Graph Completion for Recommendation System. IDEAL 2022: 188-198 - [c108]Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, Xishan Zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen:
Causality-driven Hierarchical Structure Discovery for Reinforcement Learning. NeurIPS 2022 - [c107]Fu Peng, Shengcai Liu, Ning Lu
Training Quantized Deep Neural Networks via Cooperative Coevolution. ICSI (2) 2022: 81-93 - 2021
- [c106]Chang Cao, Xiaofen Lu, Yachen Li, Junda Zhu, Ke Tang:
The Performance Effect of Model Accuracy on Classification-Assisted Evolutionary Algorithms. CEC 2021: 1527-1536 - [c105]Chengbin Hou
Towards Robust Dynamic Network Embedding. IJCAI 2021: 4889-4890 - [c104]Qi Yang
Parallel Random Embedding with Negatively Correlated Search. ICSI (2) 2021: 339-351 - 2020
- [c103]Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao:
On Performance Estimation in Automatic Algorithm Configuration. AAAI 2020: 2384-2391 - [c102]Wenjing Hong, Peng Yang, Yiwen Wang, Ke Tang:
Multi-objective Magnitude-Based Pruning for Latency-Aware Deep Neural Network Compression. PPSN (1) 2020: 470-483 - [c101]Xiaofen Lu, Ke Tang, Stefan Menzel, Xin Yao:
A Competitive Co-evolutionary optimization Method for the Dynamic Vehicle Routing Problem. SSCI 2020: 305-312 - 2019
- [c100]Shengcai Liu, Ke Tang, Xin Yao:
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. AAAI 2019: 1560-1567 - [c99]Chao Feng, Chao Qian, Ke Tang:
Unsupervised Feature Selection by Pareto Optimization. AAAI 2019: 3534-3541 - [c98]Weiming Liu, Yinda Zhou, Bin Li, Ke Tang:
Cooperative Co-evolution with Soft Grouping for Large Scale Global Optimization. CEC 2019: 318-325 - [c97]Dongbin Jiao
Optimal Energy-Delay Scheduling for Energy Harvesting WSNs via Negatively Correlated Search. ICC 2019: 1-7 - [c96]Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou:
Optimal Stochastic and Online Learning with Individual Iterates. NeurIPS 2019: 5416-5426 - [c95]Liangpeng Zhang, Ke Tang, Xin Yao:
Explicit Planning for Efficient Exploration in Reinforcement Learning. NeurIPS 2019: 7486-7495 - 2018
- [c94]Chao Qian, Yibo Zhang, Ke Tang, Xin Yao:
On Multiset Selection With Size Constraints. AAAI 2018: 1395-1402 - [c93]Chao Qian, Chao Bian, Yang Yu, Ke Tang, Xin Yao
Analysis of noisy evolutionary optimization when sampling fails. GECCO 2018: 1507-1514 - [c92]Mengxi Wu, Chao Qian, Ke Tang:
Dynamic Mutation Based Pareto Optimization for Subset Selection. ICIC (3) 2018: 25-35 - [c91]Wu Jiang, Chao Qian, Ke Tang:
Improved Running Time Analysis of the (1+1)-ES on the Sphere Function. ICIC (1) 2018: 729-739 - [c90]Chao Bian, Chao Qian, Ke Tang:
A General Approach to Running Time Analysis of Multi-objective Evolutionary Algorithms. IJCAI 2018: 1405-1411 - [c89]Chao Qian, Yang Yu, Ke Tang:
Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection. IJCAI 2018: 1478-1484 - [c88]Chao Qian, Chao Feng, Ke Tang:
Sequence Selection by Pareto Optimization. IJCAI 2018: 1485-1491 - [c87]Chao Qian, Guiying Li
Distributed Pareto Optimization for Subset Selection. IJCAI 2018: 1492-1498 - [c86]Chunhui Jiang, Guiying Li
Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error. IJCAI 2018: 2298-2304 - [c85]Yunwen Lei
Generalization Bounds for Regularized Pairwise Learning. IJCAI 2018: 2376-2382 - [c84]Guiying Li
Optimization based Layer-wise Magnitude-based Pruning for DNN Compression. IJCAI 2018: 2383-2389 - [c83]Yunwen Lei, Ke Tang:
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities. NeurIPS 2018: 1526-1536 - [c82]Chao Bian, Chao Qian, Ke Tang:
Towards a Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes Under General Bit-Wise Noise. PPSN (2) 2018: 165-177 - [c81]Dongjun Qian, Peng Yang, Ke Tang:
A Fast Heuristic Path Computation Algorithm for the Batch Bandwidth Constrained Routing Problem in SDN. PRICAI (1) 2018: 490-502 - 2017
- [c80]Yunzhou Zhang, Bo Yuan, Ke Tang:
Enhanced Pairwise Learning for Personalized Ranking from Implicit Feedback. BIC-TA 2017: 580-595 - [c79]Chao Qian, Chao Bian, Wu Jiang, Ke Tang:
Running time analysis of the (1+1)-EA for onemax and leadingones under bit-wise noise. GECCO 2017: 1399-1406 - [c78]Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, Zhi-Hua Zhou:
Optimizing Ratio of Monotone Set Functions. IJCAI 2017: 2606-2612 - [c77]Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang:
On Subset Selection with General Cost Constraints. IJCAI 2017: 2613-2619 - [c76]Ge Xie, Yu Sun, Minlong Lin, Ke Tang:
A Selective Transfer Learning Method for Concept Drift Adaptation. ISNN (2) 2017: 353-361 - [c75]Guiying Li, Junlong Liu, Chunhui Jiang, Liangpeng Zhang, Minlong Lin, Ke Tang:
Relief R-CNN: Utilizing Convolutional Features for Fast Object Detection. ISNN (1) 2017: 386-394 - [c74]Liangpeng Zhang, Ke Tang, Xin Yao:
Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning. NIPS 2017: 1804-1814 - [c73]Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, Zhi-Hua Zhou:
Subset Selection under Noise. NIPS 2017: 3560-3570 - 2016
- [c72]Yu Sun, Ke Tang:
Incremental Learning with Concept Drift: A Knowledge Transfer Perspective. BIC-TA (1) 2016: 473-479 - [c71]Bingdong Li, Chao Qian, Jinlong Li, Ke Tang, Xin Yao
Search based recommender system using many-objective evolutionary algorithm. CEC 2016: 120-126 - [c70]Peng Yang, Guanzhou Lu, Ke Tang, Xin Yao
A multi-modal optimization approach to single path planning for unmanned aerial vehicle. CEC 2016: 1735-1742 - [c69]Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, Zhi-Hua Zhou:
Parallel Pareto Optimization for Subset Selection. IJCAI 2016: 1939-1945 - [c68]Jiayi Fu, Jinhong Zhong, Yunfeng Liu, Zhenyu Wang, Ke Tang:
A non-parametric approach for learning from crowds. IJCNN 2016: 2228-2235 - [c67]Chunhui Jiang, Guiying Li
A trajectory-based approach for object detection from video. IJCNN 2016: 2887-2893 - [c66]Xiaofen Lu, Ke Tang, Xin Yao
Speciated Evolutionary Algorithm for Dynamic Constrained Optimisation. PPSN 2016: 203-213 - [c65]Zhilei Ren, He Jiang, Jifeng Xuan
Analyzing Inter-objective Relationships: A Case Study of Software Upgradability. PPSN 2016: 442-452 - [c64]Chao Qian, Ke Tang, Zhi-Hua Zhou:
Selection Hyper-heuristics Can Provably Be Helpful in Evolutionary Multi-objective Optimization. PPSN 2016: 835-846 - 2015
- [c63]Chen Jin, A. Kai Qin
Local ensemble surrogate assisted crowding differential evolution. CEC 2015: 433-440 - [c62]Wenjing Hong, Guanzhou Lu, Peng Yang, Yong Wang, Ke Tang:
A new Evolutionary multi-objective algorithm for Convex Hull Maximization. CEC 2015: 931-938 - [c61]Yuzhou Wu, Yu Sun, Xinle Liang, Ke Tang, Zixing Cai:
Evolutionary semi-supervised ordinal regression using weighted kernel Fisher discriminant analysis. CEC 2015: 3279-3286 - [c60]Shengcai Liu, Yufan Wei, Ke Tang, A. Kai Qin
QoS-aware long-term based service composition in cloud computing. CEC 2015: 3362-3369 - [c59]Guanbo Jia, Shan He, Zexuan Zhu, Jing Liu
A Multimodal Optimization and Surprise Based Consensus Community Detection Algorithm. GECCO (Companion) 2015: 1407-1408 - [c58]Jinhong Zhong, Ke Tang, Zhi-Hua Zhou:
Active Learning from Crowds with Unsure Option. IJCAI 2015: 1061-1068 - [c57]Liangpeng Zhang, Ke Tang, Xin Yao:
Increasingly Cautious Optimism for Practical PAC-MDP Exploration. IJCAI 2015: 4033-4040 - 2014
- [c56]A. Kai Qin
Self-adaptive differential evolution with local search chains for real-parameter single-objective optimization. IEEE Congress on Evolutionary Computation 2014: 467-474 - [c55]Peng Yang, Ke Tang, José Antonio Lozano:
Estimation of Distribution Algorithms based Unmanned Aerial Vehicle path planner using a new coordinate system. IEEE Congress on Evolutionary Computation 2014: 1469-1476 - [c54]Haobo Fu, Peter R. Lewis
What are dynamic optimization problems? IEEE Congress on Evolutionary Computation 2014: 1550-1557 - [c53]Thomas Weise, Mingxu Wan, Ke Tang, Xin Yao
Evolving exact integer algorithms with Genetic Programming. IEEE Congress on Evolutionary Computation 2014: 1816-1823 - [c52]Bingdong Li, Jinlong Li, Ke Tang, Xin Yao
An improved Two Archive Algorithm for Many-Objective optimization. IEEE Congress on Evolutionary Computation 2014: 2869-2876 - [c51]Jinhong Zhong, Ke Tang, A. Kai Qin
Finding convex hull vertices in metric space. IJCNN 2014: 1587-1592 - [c50]Tianshi Chen, Qi Guo, Ke Tang, Olivier Temam, Zhiwei Xu, Zhi-Hua Zhou, Yunji Chen
ArchRanker: A ranking approach to design space exploration. ISCA 2014: 85-96 - [c49]Xiaofen Lu, Stefan Menzel, Ke Tang, Xin Yao:
The Performance Effects of Interaction Frequency in Parallel Cooperative Coevolution. SEAL 2014: 82-93 - 2013
- [c48]Wenxiang Chen, Ke Tang:
Impact of problem decomposition on Cooperative Coevolution. IEEE Congress on Evolutionary Computation 2013: 733-740 - [c47]Mingzhi Li, Rui Wang, Ke Tang:
Combining Semi-Supervised and active learning for hyperspectral image classification. CIDM 2013: 89-94 - [c46]Haobo Fu, Bernhard Sendhoff, Ke Tang, Xin Yao:
Finding Robust Solutions to Dynamic Optimization Problems. EvoApplications 2013: 616-625 - [c45]Rui Wang, Weishan Dong, Yu Wang, Ke Tang, Xin Yao
Pipe failure prediction: A data mining method. ICDE 2013: 1208-1218 - [c44]Jinpeng Liu, Ke Tang:
Scaling Up Covariance Matrix Adaptation Evolution Strategy Using Cooperative Coevolution. IDEAL 2013: 350-357 - [c43]Lunjun Wan, Ke Tang, Rui Wang:
Gradient Boosting-Based Negative Correlation Learning. IDEAL 2013: 358-365 - [c42]Lili Zhuang, Ke Tang, Yaochu Jin
Metamodel Assisted Mixed-Integer Evolution Strategies Based on Kendall Rank Correlation Coefficient. IDEAL 2013: 366-375 - [c41]Zhigao Miao, Ke Tang:
Semi-supervised Ranking via List-Wise Approach. IDEAL 2013: 376-383 - [c40]Juan Wang, Ke Tang, Xin Yao
A memetic algorithm for uncertain Capacitated Arc Routing Problems. Memetic Computing 2013: 72-79 - 2012
- [c39]Haobo Fu, Bernhard Sendhoff
Characterizing environmental changes in Robust Optimization Over Time. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c38]Thomas Weise, Alexandre Devert, Ke Tang:
A developmental solution to (dynamic) capacitated arc routing problems using genetic programming. GECCO 2012: 831-838 - [c37]Xiaoxing Yang, Ke Tang, Xin Yao
A Learning-to-Rank Algorithm for Constructing Defect Prediction Models. IDEAL 2012: 167-175 - [c36]Qiang Huang
Community Detection Using Cooperative Co-evolutionary Differential Evolution. PPSN (2) 2012: 235-244 - 2011
- [c35]Ke Tang, Rui Wang, Tianshi Chen:
Towards Maximizing the Area Under the ROC Curve for Multi-Class Classification Problems. AAAI 2011: 483-488 - [c34]Pu Wang, Ke Tang, Edward P. K. Tsang, Xin Yao
A Memetic Genetic Programming with decision tree-based local search for classification problems. IEEE Congress on Evolutionary Computation 2011: 917-924 - [c33]Xiaofen Lu, Ke Tang, Xin Yao
Classification-assisted Differential Evolution for computationally expensive problems. IEEE Congress on Evolutionary Computation 2011: 1986-1993 - [c32]Mingxu Wan, Thomas Weise, Ke Tang:
Novel Loop Structures and the Evolution of Mathematical Algorithms. EuroGP 2011: 49-60 - [c31]Fei Peng, Ke Tang:
Alleviate the Hypervolume Degeneration Problem of NSGA-II. ICONIP (2) 2011: 425-434 - [c30]Mingming Xiao, Jun Zhang, Kaiquan Cai, Xianbin Cao, Ke Tang:
Cooperative Co-evolution with Weighted Random Grouping for Large-Scale Crossing Waypoints Locating in Air Route Network. ICTAI 2011: 215-222 - [c29]Xiannian Fan, Ke Tang, Thomas Weise:
Margin-Based Over-Sampling Method for Learning from Imbalanced Datasets. PAKDD (2) 2011: 309-320 - [c28]Lisong Chen, Huanhuan Chen, Ke Tang:
Semi-supervised learning with extremely sparse labeled data on multiple semi-supervised assumptions. SoCPaR 2011: 242-247 - 2010
- [c27]Pu Wang, Edward P. K. Tsang, Thomas Weise, Ke Tang, Xin Yao
Using GP to evolve decision rules for classification in financial data sets. IEEE ICCI 2010: 720-727 - [c26]Haobo Fu, Yi Mei
Memetic algorithm with heuristic candidate list strategy for Capacitated Arc Routing Problem. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c25]Yi Mei
Capacitated arc routing problem in uncertain environments. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c24]Xin Yu, Yaochu Jin
Robust optimization over time - A new perspective on dynamic optimization problems. IEEE Congress on Evolutionary Computation 2010: 1-6 - [c23]Xiannian Fan, Ke Tang:
Enhanced Maximum AUC Linear Classifier. FSKD 2010: 1540-1544 - [c22]Thomas Weise, Li Niu, Ke Tang:
AOAB: automated optimization algorithm benchmarking. GECCO (Companion) 2010: 1479-1486 - [c21]Xiaofen Lu, Ke Tang, Xin Yao
Evolving Neural Networks with Maximum AUC for Imbalanced Data Classification. HAIS (1) 2010: 335-342 - [c20]Wenxiang Chen, Thomas Weise, Zhenyu Yang, Ke Tang:
Large-Scale Global Optimization Using Cooperative Coevolution with Variable Interaction Learning. PPSN (2) 2010: 300-309 - [c19]Xin Yu, Thomas Weise, Ke Tang, Steffen Bleul:
QoS-aware semantic web service composition for SOAs. SOCA 2010: 1-4 - 2009
- [c18]Zhenyu Yang, Jingqiao Zhang, Ke Tang, Xin Yao
An adaptive coevolutionary Differential Evolution algorithm for large-scale optimization. IEEE Congress on Evolutionary Computation 2009: 102-109 - [c17]Zai Wang, Tianshi Chen, Ke Tang, Xin Yao
A multi-objective approach to Redundancy Allocation Problem in parallel-series systems. IEEE Congress on Evolutionary Computation 2009: 582-589 - [c16]Yunji Chen
A stochastic method for controlling the scaling parameters of Cauchy mutation in fast evolutionary programming. IEEE Congress on Evolutionary Computation 2009: 1101-1107 - [c15]Tianshi Chen, Per Kristian Lehre
When is an estimation of distribution algorithm better than an evolutionary algorithm? IEEE Congress on Evolutionary Computation 2009: 1470-1477 - [c14]Yi Mei
Improved memetic algorithm for Capacitated Arc Routing Problem. IEEE Congress on Evolutionary Computation 2009: 1699-1706 - [c13]Fei Peng, Ke Tang, Guoliang Chen, Xin Yao
Multi-start JADE with knowledge transfer for numerical optimization. IEEE Congress on Evolutionary Computation 2009: 1889-1895 - [c12]Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao
Rigorous time complexity analysis of Univariate Marginal Distribution Algorithm with margins. IEEE Congress on Evolutionary Computation 2009: 2157-2164 - [c11]Rui Wang, Ke Tang:
Feature Selection for Maximizing the Area Under the ROC Curve. ICDM Workshops 2009: 400-405 - [c10]Xiaoxing Yang, Ke Tang, Xin Yao
The Minimum Redundancy - Maximum Relevance Approach to Building Sparse Support Vector Machines. IDEAL 2009: 184-190 - [c9]Shuo Wang, Ke Tang, Xin Yao
Diversity exploration and negative correlation learning on imbalanced data sets. IJCNN 2009: 3259-3266 - 2008
- [c8]Zhenyu Yang, Ke Tang, Xin Yao
Self-adaptive differential evolution with neighborhood search. IEEE Congress on Evolutionary Computation 2008: 1110-1116 - [c7]Xin Yu, Ke Tang, Xin Yao
An immigrants scheme based on environmental information for genetic algorithms in changing environments. IEEE Congress on Evolutionary Computation 2008: 1141-1147 - [c6]Zai Wang, Ke Tang, Xin Yao
A multi-objective approach to testing resource allocation in modular software systems. IEEE Congress on Evolutionary Computation 2008: 1148-1153 - [c5]Zhenyu Yang, Ke Tang, Xin Yao
Multilevel cooperative coevolution for large scale optimization. IEEE Congress on Evolutionary Computation 2008: 1663-1670 - [c4]Ke Tang, Zai Wang, Xianbin Cao, Jun Zhang:
A multi-objective evolutionary approach to aircraft landing scheduling problems. IEEE Congress on Evolutionary Computation 2008: 3650-3656 - [c3]Minlong Lin, Ke Tang, Xin Yao
Selective negative correlation learning algorithm for incremental learning. IJCNN 2008: 2525-2530 - 2007
- [c2]Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao
On the analysis of average time complexity of estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2007: 453-460 - [c1]Zhenyu Yang, Ke Tang, Xin Yao
Differential evolution for high-dimensional function optimization. IEEE Congress on Evolutionary Computation 2007: 3523-3530
Editorship
- 2021
- [e5]Hujun Yin
Intelligent Data Engineering and Automated Learning - IDEAL 2021 - 22nd International Conference, IDEAL 2021, Manchester, UK, November 25-27, 2021, Proceedings. Lecture Notes in Computer Science 13113, Springer 2021, ISBN 978-3-030-91607-7 [contents] - 2017
- [e4]Yuhui Shi, Kay Chen Tan, Mengjie Zhang, Ke Tang, Xiaodong Li, Qingfu Zhang, Ying Tan, Martin Middendorf, Yaochu Jin:
Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10-13, 2017, Proceedings. Lecture Notes in Computer Science 10593, Springer 2017, ISBN 978-3-319-68758-2 [contents] - 2015
- [e3]Maoguo Gong, Linqiang Pan, Tao Song, Ke Tang, Xingyi Zhang:
Bio-Inspired Computing - Theories and Applications - 10th International Conference, BIC-TA 2015, Hefei, China, September 25-28, 2015, Proceedings. Communications in Computer and Information Science 562, Springer 2015, ISBN 978-3-662-49013-6 [contents] - 2014
- [e2]Grant Dick, Will N. Browne, Peter A. Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang:
Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings. Lecture Notes in Computer Science 8886, Springer 2014, ISBN 978-3-319-13562-5 [contents] - 2013
- [e1]Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Thomas Weise, Bin Li, Xin Yao:
Intelligent Data Engineering and Automated Learning - IDEAL 2013 - 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013. Proceedings. Lecture Notes in Computer Science 8206, Springer 2013, ISBN 978-3-642-41277-6 [contents]
Informal and Other Publications
- 2025
- [i81]Zhiyuan Wang, Shengcai Liu, Peng Yang, Ke Tang:
Domain-Agnostic Co-Evolution of Generalizable Parallel Algorithm Portfolios. CoRR abs/2501.02906 (2025) - [i80]Ziming Wang, Changwu Huang, Ke Tang, Xin Yao:
Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning. CoRR abs/2501.06753 (2025) - [i79]Shengcai Liu, Haoze Lv, Zhiyuan Wang, Ke Tang:
Cascaded Large-Scale TSP Solving with Unified Neural Guidance: Bridging Local and Population-based Search. CoRR abs/2501.14285 (2025) - [i78]Kunlong Zhang, Guiying Li, Ning Lu
Hardware-Aware DNN Compression for Homogeneous Edge Devices. CoRR abs/2501.15240 (2025) - [i77]Jiarui Song, Yunheng Shen, Chengbin Hou, Pengyu Wang, Jinbao Wang, Ke Tang, Hairong Lv:
FedAGHN: Personalized Federated Learning with Attentive Graph HyperNetworks. CoRR abs/2501.16379 (2025) - [i76]Peng Yang, Junji Ren, Feng Wang, Ke Tang:
Towards Calibrating Financial Market Simulators with High-frequency Data. CoRR abs/2504.00538 (2025) - [i75]Rui Xu, Xing Fan, Shengcai Liu, Wenjie Chen, Ke Tang:
Memetic Search for Green Vehicle Routing Problem with Private Capacitated Refueling Stations. CoRR abs/2504.04527 (2025) - [i74]Zeyu Dai, Shengcai Liu, Rui He, Jiahao Wu, Ning Lu
SemDiff: Generating Natural Unrestricted Adversarial Examples via Semantic Attributes Optimization in Diffusion Models. CoRR abs/2504.11923 (2025) - [i73]Ning Lu, Shengcai Liu, Jiahao Wu, Weiyu Chen, Zhirui Zhang, Yew-Soon Ong, Qi Wang, Ke Tang:
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets. CoRR abs/2505.12038 (2025) - [i72]Bingdong Li, Mei Jiang, Hong Qian, Ke Tang, Aimin Zhou, Peng Yang:
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network. CoRR abs/2505.19423 (2025) - [i71]Shaofeng Zhang, Shengcai Liu, Ning Lu, Jiahao Wu, Ji Liu, Yew-Soon Ong, Ke Tang:
LLM-Driven Instance-Specific Heuristic Generation and Selection. CoRR abs/2506.00490 (2025) - [i70]Shengcai Liu, Hui Ouyang, Zhiyuan Wang, Cheng Chen, Qijun Cai, Yew-Soon Ong, Ke Tang:
Scalable Structure Learning of Bayesian Networks by Learning Algorithm Ensembles. CoRR abs/2506.22848 (2025) - 2024
- [i69]Tianyu Zhang, Chengbin Hou, Rui Jiang, Xuegong Zhang, Chenghu Zhou, Ke Tang, Hairong Lv:
Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs. CoRR abs/2402.17791 (2024) - [i68]Yongfan Lu, Zixiang Di, Bingdong Li, Shengcai Liu, Hong Qian, Peng Yang, Ke Tang, Aimin Zhou:
Towards Geometry-Aware Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization. CoRR abs/2405.08604 (2024) - [i67]Bingdong Li, Zixiang Di, Yongfan Lu, Hong Qian, Feng Wang, Peng Yang, Ke Tang, Aimin Zhou:
Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models. CoRR abs/2405.08674 (2024) - [i66]Shengcai Liu, Zhiyuan Wang, Yew-Soon Ong, Xin Yao, Ke Tang:
Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization. CoRR abs/2405.18884 (2024) - [i65]Bingdong Li, Zixiang Di, Yanting Yang, Hong Qian, Peng Yang, Hao Hao, Ke Tang, Aimin Zhou:
It's Morphing Time: Unleashing the Potential of Multiple LLMs via Multi-objective Optimization. CoRR abs/2407.00487 (2024) - [i64]Jiahao Wu, Ning Lu, Zeiyu Dai, Wenqi Fan, Shengcai Liu, Qing Li, Ke Tang:
Backdoor Graph Condensation. CoRR abs/2407.11025 (2024) - [i63]Wenhao Mao, Chengbin Hou, Tianyu Zhang, Xinyu Lin, Ke Tang, Hairong Lv:
Parse Trees Guided LLM Prompt Compression. CoRR abs/2409.15395 (2024) - 2023
- [i62]Lan Tang, Xiaxi Li, Jinyuan Zhang, Guiying Li, Peng Yang, Ke Tang:
Enabling surrogate-assisted evolutionary reinforcement learning via policy embedding. CoRR abs/2301.13374 (2023) - [i61]Ning Lu
Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend. CoRR abs/2302.02568 (2023) - [i60]Rui He, Shengcai Liu, Jiahao Wu, Shan He, Ke Tang:
Multi-Domain Learning From Insufficient Annotations. CoRR abs/2305.02757 (2023) - [i59]Ning Lu
Large Language Models can be Guided to Evade AI-Generated Text Detection. CoRR abs/2305.10847 (2023) - [i58]Rui He, Zeyu Dai, Shan He, Ke Tang:
Perturbation-Based Two-Stage Multi-Domain Active Learning. CoRR abs/2306.10700 (2023) - [i57]Xuanfeng Li, Shengcai Liu, Jin Wang, Xiao Chen, Yew-Soon Ong, Ke Tang:
Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. CoRR abs/2306.14690 (2023) - [i56]Wenjie Chen, Shengcai Liu, Yew-Soon Ong, Ke Tang:
Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization. CoRR abs/2308.14012 (2023) - [i55]Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Qing Li, Ke Tang:
Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling. CoRR abs/2309.12723 (2023) - [i54]Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, Ke Tang:
Dataset Condensation for Recommendation. CoRR abs/2310.01038 (2023) - [i53]Dan-Xuan Liu, Yu-Ran Gu
Migrant Resettlement by Evolutionary Multi-objective Optimization. CoRR abs/2310.08896 (2023) - [i52]Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang:
Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation. CoRR abs/2310.09874 (2023) - [i51]Shengcai Liu, Caishun Chen, Xinghua Qu, Ke Tang, Yew-Soon Ong:
Large Language Models as Evolutionary Optimizers. CoRR abs/2310.19046 (2023) - [i50]Shaofeng Zhang, Shengcai Liu, Ke Tang:
A Sample Reuse Strategy for Dynamic Influence Maximization Problem. CoRR abs/2311.15345 (2023) - [i49]Muyao Zhong, Shengcai Liu, Bingdong Li, Haobo Fu, Ke Tang, Peng Yang:
Pointer Networks Trained Better via Evolutionary Algorithms. CoRR abs/2312.01150 (2023) - [i48]Hui Ouyang, Cheng Chen, Ke Tang:
Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning. CoRR abs/2312.01739 (2023) - 2022
- [i47]Dongbin Jiao, Lingyu Wang, Peng Yang, Weibo Yang, Yu Peng, Zhanhuan Shang, Ke Tang, Fengyuan Ren:
Near-Optimal Trajectory Design and Restoration Areas Allocation for UAV-Enabled Grassland Restoration. CoRR abs/2204.04666 (2022) - [i46]Zeyu Dai, Shengcai Liu, Ke Tang, Qing Li:
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. CoRR abs/2206.01898 (2022) - [i45]Wenjian Luo, Hongwei Zhang, Linghao Kong, Zhijian Chen, Ke Tang:
Defending Adversarial Examples by Negative Correlation Ensemble. CoRR abs/2206.10334 (2022) - [i44]Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qing Li, Ke Tang:
Disentangled Contrastive Learning for Social Recommendation. CoRR abs/2208.08723 (2022) - [i43]Shengcai Liu, Yu Zhang, Ke Tang, Xin Yao:
How Good Is Neural Combinatorial Optimization? CoRR abs/2209.10913 (2022) - [i42]Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, Xishan Zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen:
Causality-driven Hierarchical Structure Discovery for Reinforcement Learning. CoRR abs/2210.06964 (2022) - [i41]Shengcai Liu, Fu Peng, Ke Tang:
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. CoRR abs/2211.12713 (2022) - 2021
- [i40]Wenjie Chen, Shengcai Liu, Ke Tang:
A New Knowledge Gradient-based Method for Constrained Bayesian Optimization. CoRR abs/2101.08743 (2021) - [i39]Chao Qian, Dan-Xuan Liu, Chao Feng, Ke Tang:
Multi-objective Evolutionary Algorithms are Generally Good: Maximizing Monotone Submodular Functions over Sequences. CoRR abs/2104.09884 (2021) - [i38]Chengbin Hou
Robust Dynamic Network Embedding via Ensembles. CoRR abs/2105.14557 (2021) - [i37]Rui He, Shan He, Ke Tang:
Multi-Domain Active Learning: A Comparative Study. CoRR abs/2106.13516 (2021) - [i36]Shengcai Liu, Ning Lu, Cheng Chen, Ke Tang:
Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack. CoRR abs/2109.02229 (2021) - [i35]Shengcai Liu, Ning Lu, Cheng Chen, Chao Qian, Ke Tang:
HydraText: Multi-objective Optimization for Adversarial Textual Attack. CoRR abs/2111.01528 (2021) - [i34]Fu Peng, Shengcai Liu, Ning Lu, Ke Tang:
Training Quantized Deep Neural Networks via Cooperative Coevolution. CoRR abs/2112.14834 (2021) - 2020
- [i33]Ke Tang, Shengcai Liu, Peng Yang, Xin Yao:
Few-shots Parameter Tuning via Co-evolution. CoRR abs/2007.00501 (2020) - [i32]Chengbin Hou, Han Zhang, Shan He, Ke Tang:
GloDyNE: Global Topology Preserving Dynamic Network Embedding. CoRR abs/2008.01935 (2020) - [i31]Hu Zhang, Peng Yang, Yanglong Yu, Mingjia Li, Ke Tang:
Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search. CoRR abs/2009.03603 (2020) - [i30]Shengcai Liu, Ke Tang, Xin Yao:
Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows. CoRR abs/2011.06331 (2020) - [i29]Yu Zhang, Peter Tiño, Ales Leonardis, Ke Tang:
A Survey on Neural Network Interpretability. CoRR abs/2012.14261 (2020) - 2019
- [i28]Yunwen Lei, Ting Hu, Ke Tang:
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions. CoRR abs/1902.00908 (2019) - [i27]Chao Bian, Chao Qian, Ke Tang:
Running Time Analysis of the (1+1)-EA for Robust Linear Optimization. CoRR abs/1906.06873 (2019) - [i26]Chengbin Hou
DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding. CoRR abs/1907.11968 (2019) - [i25]Xiaofen Lu, Ke Tang, Stefan Menzel, Xin Yao:
Competitive Co-evolution for Dynamic Constrained Optimisation. CoRR abs/1907.13529 (2019) - [i24]Peng Yang, Ke Tang, Xin Yao:
Negatively Correlated Search as a Parallel Exploration Search Strategy. CoRR abs/1910.07151 (2019) - [i23]Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao:
On Performance Estimation in Automatic Algorithm Configuration. CoRR abs/1911.08200 (2019) - 2018
- [i22]Shengcai Liu, Ke Tang, Xin Yao:
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. CoRR abs/1804.06088 (2018) - [i21]Chao Qian, Chao Bian, Yang Yu, Ke Tang, Xin Yao:
Analysis of Noisy Evolutionary Optimization When Sampling Fails. CoRR abs/1810.05045 (2018) - [i20]Yibo Zhang, Chao Qian, Ke Tang:
Maximizing Monotone DR-submodular Continuous Functions by Derivative-free Optimization. CoRR abs/1810.06833 (2018) - [i19]Chengbin Hou, Shan He, Ke Tang:
Attributed Network Embedding for Incomplete Structure Information. CoRR abs/1811.11728 (2018) - [i18]Peng Yang, Ke Tang, Xin Yao:
A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization. CoRR abs/1812.02500 (2018) - 2017
- [i17]Yu Sun, Ke Tang, Zexuan Zhu, Xin Yao:
Concept Drift Adaptation by Exploiting Historical Knowledge. CoRR abs/1702.03500 (2017) - [i16]Zhi-Zhong Liu, Yong Wang, Shengxiang Yang, Ke Tang:
An Adaptive Framework to Tune the Coordinate Systems in Evolutionary Algorithms. CoRR abs/1703.06263 (2017) - [i15]Shengcai Liu, Ke Tang, Xin Yao:
Experience-based Optimization: A Coevolutionary Approach. CoRR abs/1703.09865 (2017) - [i14]Bingshui Da, Yew-Soon Ong, Liang Feng, A. Kai Qin, Abhishek Gupta, Zexuan Zhu, Chuan-Kang Ting, Ke Tang, Xin Yao:
Evolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results. CoRR abs/1706.03470 (2017) - [i13]Jinyuan Zhang, Aimin Zhou, Ke Tang, Guixu Zhang:
Preselection via Classification: A Case Study on Evolutionary Multiobjective Optimization. CoRR abs/1708.01146 (2017) - [i12]Chao Qian, Chao Bian, Wu Jiang, Ke Tang:
Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes under Bit-wise Noise. CoRR abs/1711.00956 (2017) - [i11]Chao Qian, Yang Yu, Ke Tang, Xin Yao, Zhi-Hua Zhou:
Maximizing Non-monotone/Non-submodular Functions by Multi-objective Evolutionary Algorithms. CoRR abs/1711.07214 (2017) - 2016
- [i10]Guiying Li, Junlong Liu, Chunhui Jiang, Ke Tang:
Relief Impression Image Detection : Unsupervised Extracting Objects Directly From Feature Arrangements of Deep CNN. CoRR abs/1601.06719 (2016) - [i9]Peng Yang, Ke Tang, Xin Yao:
High-dimensional Black-box Optimization via Divide and Approximate Conquer. CoRR abs/1603.03518 (2016) - [i8]Liangpeng Zhang, Ke Tang, Xin Yao:
Success Probability of Exploration: a Concrete Analysis of Learning Efficiency. CoRR abs/1612.00882 (2016) - 2015
- [i7]Ke Tang, Peng Yang, Xin Yao:
Negatively Correlated Cooperative Search. CoRR abs/1504.04914 (2015) - 2013
- [i6]Pu Wang, Michael Emmerich, Rui Li, Ke Tang, Thomas Bäck, Xin Yao:
Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance. CoRR abs/1303.3145 (2013) - 2012
- [i5]Rui Wang, Ke Tang:
Minimax Classifier for Uncertain Costs. CoRR abs/1205.0406 (2012) - [i4]Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao:
A Large Population Size Can Be Unhelpful in Evolutionary Algorithms. CoRR abs/1208.2345 (2012) - [i3]Rui Wang, Ke Tang:
An Empirical Study of MAUC in Multi-class Problems with Uncertain Cost Matrices. CoRR abs/1209.1800 (2012) - 2011
- [i2]Rui Wang, Ke Tang:
Feature Selection for MAUC-Oriented Classification Systems. CoRR abs/1105.2943 (2011) - [i1]Tianshi Chen, Yunji Chen, Ke Tang, Guoliang Chen, Xin Yao:
The Impact of Mutation Rate on the Computation Time of Evolutionary Dynamic Optimization. CoRR abs/1106.0566 (2011)
Coauthor Index
[j128] [j126] [j122] [j121] [j117] [j112] [j110] [j107] [j106] [j93] [j90] [j87] [c123] [c121] [c119] [c117] [c114] [c112] [c107] [c103] [c100] [c60] [i81] [i79] [i75] [i74] [i73] [i71] [i70] [i68] [i66] [i64] [i61] [i60] [i59] [i57] [i56] [i55] [i54] [i52] [i51] [i50] [i49] [i46] [i44] [i43] [i41] [i40] [i36] [i35] [i34] [i33] [i30] [i23] [i22] [i15]
[j117] [j106] [j103] [j99] [j97] [j96] [j90] [j87] [j86] [j76] [j75] [j73] [j69] [j65] [j63] [j62] [j60] [j54] [j51] [j48] [j45] [j44] [j43] [j42] [j41] [j36] [j35] [j33] [j31] [j30] [j29] [j28] [j27] [j26] [j25] [j24] [j18] [j16] [j15] [j14] [j13] [j11] [j10] [j9] [j8] [j7] [j6] [j5] [j4] [j3] [j2] [j1] [c125] [c103] [c101] [c100] [c95] [c94] [c93] [c74] [c71] [c70] [c66] [c60] [c57] [c54] [c53] [c52] [c49] [c46] [c45] [c40] [c39] [c37] [c36] [c34] [c33] [c27] [c25] [c24] [c21] [c18] [c17] [c15] [c14] [c13] [c12] [c10] [c9] [c8] [c7] [c6] [c5] [c3] [c2] [c1] [e1] [i80] [i66] [i43] [i33] [i30] [i25] [i24] [i23] [i22] [i21] [i18] [i17] [i15] [i14] [i11] [i9] [i8] [i7] [i6] [i4] [i1]
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