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ORCIDTianye Shu
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2020 – today
- 2025
[j6]Yang Nan
, Tianye Shu, Hisao Ishibuchi, Ke Shang:
Gradient-Guided Local Search for Large-Scale Hypervolume Subset Selection. IEEE Trans. Evol. Comput. 29(2): 519-533 (2025)- [c28]Yang Nan, Hisao Ishibuchi, Tianye Shu:
Shape of Feasible Regions of Real-World Multi-Objective Problems. CEC 2025: 1-7 - [c27]Ke Shang, Tianye Shu, Yang Nan, Lie Meng Pang, Hisao Ishibuchi:
On the Quality of Large Non-dominated Archives. CEC 2025: 1-4 - [c26]Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Numerical Analysis of Pareto Set Modeling. EMO (2) 2025: 17-30 - [c25]Hisao Ishibuchi, Tianye Shu, Lie Meng Pang:
Scalable Multi-Modal Multi-Objective Test Problems with Respect to Decision Space Dimensionality and Pareto Set Dimensionality: High-Dimensional Manhattan Distance Minimization Problems. FOGA 2025: 118-129 - [c24]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
R2 Indicator Analysis using the Optimal Distributions of Solutions for R2 and Other Indicators. GECCO 2025: 627-635 - [c23]Tianye Shu, Hisao Ishibuchi, Lie Meng Pang:
An Inverse Model-based Solution Generation Method for Evolutionary Multi-objective Optimization Algorithms. IJCNN 2025: 1-8 - [c22]Tianye Shu, Hisao Ishibuchi, Andy Song, Yang Nan, Lie Meng Pang:
Investigation of Training-free Metrics for Multi-objective Neural Architecture Search. IJCNN 2025: 1-8 - [c21]Yang Nan, Hisao Ishibuchi, Tianye Shu, Longcan Chen:
Mutation Probability Specification in Large-Scale Evolutionary Multi-Objective Optimization Algorithms. SMC 2025: 3482-3488 - [c20]Lie Meng Pang, Tianye Shu, Hisao Ishibuchi:
Visual Tradeoff Analysis between Decision Space Diversity and Objective Space Diversity: Use of DTLZ Test Problems as Multi-Modal Multi-Objective Optimization Problems. SMC 2025: 4049-4055 - 2024
- [j5]Ziqi Wang, Tianye Shu, Jialin Liu:
State-Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning. IEEE Trans. Games 16(2): 489-492 (2024) - [j4]Ke Shang, Tianye Shu, Hisao Ishibuchi:
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. IEEE Trans. Evol. Comput. 28(1): 105-116 (2024) - [c19]Yang Nan, Hisao Ishibuchi, Tianye Shu:
Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective. CEC 2024: 1-6 - [c18]Cheng Gong, Yang Nan, Tianye Shu, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Interactive Final Solution Selection in Multi-Objective Optimization. CEC 2024: 1-9 - [c17]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms. CEC 2024: 1-8 - [c16]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms. GECCO 2024 - [c15]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Gradient-Guided Local Search for IGD/IGDPlus Subset Selection. GECCO 2024 - [c14]Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi:
Learning Pareto Set for Multi-Objective Continuous Robot Control. IJCAI 2024: 4920-4928 - [c13]Cheng Gong, Ping Guo, Tianye Shu, Qingfu Zhang, Hisao Ishibuchi:
LTR-HSS: A Learning-to-Rank Based Framework for Hypervolume Subset Selection. PPSN (4) 2024: 36-51 - [c12]Yang Nan, Hisao Ishibuchi, Tianye Shu, Cheng Gong:
On the use of the Total Constraint Violation as an Additional Objective in Evolutionary Multi-Objective Optimization. SMC 2024: 5048-5055 - [i8]Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi:
Learning Pareto Set for Multi-Objective Continuous Robot Control. CoRR abs/2406.18924 (2024) - 2023
- [j3]Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Benchmarking large-scale subset selection in evolutionary multi-objective optimization. Inf. Sci. 622: 755-770 (2023) - [j2]Chengpeng Hu, Ziqi Wang, Tianye Shu, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu:
Reinforcement Learning With Dual-Observation for General Video Game Playing. IEEE Trans. Games 15(2): 202-216 (2023) - [j1]Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan:
Effects of Archive Size on Computation Time and Solution Quality for Multiobjective Optimization. IEEE Trans. Evol. Comput. 27(4): 1145-1153 (2023) - [c11]Yang Nan, Tianye Shu, Hisao Ishibuchi:
Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems. CEC 2023: 1-8 - [c10]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems. EMO 2023: 391-404 - [c9]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets. GECCO 2023: 740-748 - [c8]Yang Nan, Tianye Shu, Hisao Ishibuchi:
Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem. SMC 2023: 1154-1161 - [c7]Ke Shang, Tianye Shu, Guotong Wu, Yang Nan, Lie Meng Pang, Hisao Ishibuchi:
Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts. SSCI 2023: 433-440 - [c6]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets. SSCI 2023: 441-448 - [c5]Guotong Wu, Tianye Shu, Ke Shang, Hisao Ishibuchi:
Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation. SSCI 2023: 449-456 - [c4]Guotong Wu, Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Ensemble R2-based Hypervolume Contribution Approximation. SSCI 2023: 1503-1510 - 2022
- [c3]Tianye Shu, Ke Shang, Yang Nan, Hisao Ishibuchi:
Direction Vector Selection for R2-Based Hypervolume Contribution Approximation. PPSN (2) 2022: 110-123 - [i7]Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2201.06700 (2022) - [i6]Ke Shang, Tianye Shu, Hisao Ishibuchi:
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. CoRR abs/2201.06707 (2022) - [i5]Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan:
Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization. CoRR abs/2209.03100 (2022) - [i4]Ziqi Wang, Tianye Shu, Jialin Liu:
State Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning. CoRR abs/2212.02951 (2022) - 2021
- [c2]Tianye Shu, Jialin Liu, Georgios N. Yannakakis:
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study. CoG 2021: 1-9 - [i3]Tianye Shu, Jialin Liu, Georgios N. Yannakakis:
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study. CoRR abs/2106.15877 (2021) - 2020
- [c1]Tianye Shu, Ziqi Wang, Jialin Liu, Xin Yao:
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros. CEC 2020: 1-10 - [i2]Tianye Shu, Ziqi Wang, Jialin Liu, Xin Yao:
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros. CoRR abs/2005.06148 (2020) - [i1]Chengpeng Hu, Ziqi Wang, Tianye Shu, Yang Tao, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu:
Robust Reinforcement Learning for General Video Game Playing. CoRR abs/2011.05622 (2020)
Coauthor Index
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