Tianye Shu

42 papers A* 1A 5B 13C 2Journal 14Unranked 7
YearRankTypeTitle / Venue / Authors
2025 B conf
An Inverse Model-based Solution Generation Method for Evolutionary Multi-objective Optimization Algorithms.
IJCNN
Tianye Shu, Hisao Ishibuchi, Lie Meng Pang
2025 J jnl
Gradient-Guided Local Search for Large-Scale Hypervolume Subset Selection.
IEEE Trans. Evol. Comput.
Yang Nan, Tianye Shu, Hisao Ishibuchi, Ke Shang
2025 B conf
Investigation of Training-free Metrics for Multi-objective Neural Architecture Search.
IJCNN
Tianye Shu, Hisao Ishibuchi, Andy Song, Yang Nan, Lie Meng Pang
2025 B conf
Mutation Probability Specification in Large-Scale Evolutionary Multi-Objective Optimization Algorithms.
SMC
Yang Nan, Hisao Ishibuchi, Tianye Shu, Longcan Chen
2025 — conf
Numerical Analysis of Pareto Set Modeling.
EMO (2)
Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang
2025 B conf
On the Quality of Large Non-dominated Archives.
CEC
Ke Shang, Tianye Shu, Yang Nan, Lie Meng Pang, Hisao Ishibuchi
2025 A conf
R2 Indicator Analysis using the Optimal Distributions of Solutions for R2 and Other Indicators.
GECCO
Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang
2025 A conf
Scalable Multi-Modal Multi-Objective Test Problems with Respect to Decision Space Dimensionality and Pareto Set Dimensionality: High-Dimensional Manhattan Distance Minimization Problems.
FOGA
Hisao Ishibuchi, Tianye Shu, Lie Meng Pang
2025 B conf
Shape of Feasible Regions of Real-World Multi-Objective Problems.
CEC
Yang Nan, Hisao Ishibuchi, Tianye Shu
2025 B conf
Visual Tradeoff Analysis between Decision Space Diversity and Objective Space Diversity: Use of DTLZ Test Problems as Multi-Modal Multi-Objective Optimization Problems.
SMC
Lie Meng Pang, Tianye Shu, Hisao Ishibuchi
2024 A conf
Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms.
GECCO
Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang
2024 A conf
Gradient-Guided Local Search for IGD/IGDPlus Subset Selection.
GECCO
Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang
2024 B conf
Interactive Final Solution Selection in Multi-Objective Optimization.
CEC
Cheng Gong, Yang Nan, Tianye Shu, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang
2024 — conf
LTR-HSS: A Learning-to-Rank Based Framework for Hypervolume Subset Selection.
PPSN (4)
Cheng Gong, Ping Guo, Tianye Shu, Qingfu Zhang, Hisao Ishibuchi
2024 B conf
Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms.
CEC
Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi
2024 A* conf
Learning Pareto Set for Multi-Objective Continuous Robot Control.
IJCAI
Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi
2024 J jnl
Learning Pareto Set for Multi-Objective Continuous Robot Control.
CoRR
Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi
2024 J jnl
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation.
IEEE Trans. Evol. Comput.
Ke Shang, Tianye Shu, Hisao Ishibuchi
2024 B conf
On the use of the Total Constraint Violation as an Additional Objective in Evolutionary Multi-Objective Optimization.
SMC
Yang Nan, Hisao Ishibuchi, Tianye Shu, Cheng Gong
2024 B conf
Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective.
CEC
Yang Nan, Hisao Ishibuchi, Tianye Shu
2024 J jnl
State-Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning.
IEEE Trans. Games
Ziqi Wang, Tianye Shu, Jialin Liu
2023 — conf
Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets.
SSCI
Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi
2023 J jnl
Benchmarking large-scale subset selection in evolutionary multi-objective optimization.
Inf. Sci.
Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang
2023 J jnl
Effects of Archive Size on Computation Time and Solution Quality for Multiobjective Optimization.
IEEE Trans. Evol. Comput.
Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan
2023 B conf
Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems.
CEC
Yang Nan, Tianye Shu, Hisao Ishibuchi
2023 — conf
Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts.
SSCI
Ke Shang, Tianye Shu, Guotong Wu, Yang Nan, Lie Meng Pang, Hisao Ishibuchi
2023 — conf
Ensemble R2-based Hypervolume Contribution Approximation.
SSCI
Guotong Wu, Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi
2023 — conf
Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation.
SSCI
Guotong Wu, Tianye Shu, Ke Shang, Hisao Ishibuchi
2023 J jnl
Reinforcement Learning With Dual-Observation for General Video Game Playing.
IEEE Trans. Games
Chengpeng Hu, Ziqi Wang, Tianye Shu, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu
2023 A conf
Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets.
GECCO
Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi
2023 C conf
Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems.
EMO
Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang
2023 B conf
Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem.
SMC
Yang Nan, Tianye Shu, Hisao Ishibuchi
2022 J jnl
Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization.
CoRR
Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang
2022 — conf
Direction Vector Selection for R2-Based Hypervolume Contribution Approximation.
PPSN (2)
Tianye Shu, Ke Shang, Yang Nan, Hisao Ishibuchi
2022 J jnl
Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization.
CoRR
Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan
2022 J jnl
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation.
CoRR
Ke Shang, Tianye Shu, Hisao Ishibuchi
2022 J jnl
State Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning.
CoRR
Ziqi Wang, Tianye Shu, Jialin Liu
2021 C conf
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study.
CoG
Tianye Shu, Jialin Liu, Georgios N. Yannakakis
2021 J jnl
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study.
CoRR
Tianye Shu, Jialin Liu, Georgios N. Yannakakis
2020 B conf
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros.
CEC
Tianye Shu, Ziqi Wang, Jialin Liu, Xin Yao
2020 J jnl
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros.
CoRR
Tianye Shu, Ziqi Wang, Jialin Liu, Xin Yao
2020 J jnl
Robust Reinforcement Learning for General Video Game Playing.
CoRR
Chengpeng Hu, Ziqi Wang, Tianye Shu, Yang Tao, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu