Ye Tian
Artificial Intelligence · IEEE Transactions on Evolutionary Computation · 2015–2021
A researcher in the Science corpus: 13 papers; trusts 106 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 305 citations into it; #6,198 of 35,345 by trust here, #9,170 by citations
- Computational Theory and Mathematics — 305 citations into it; #1,261 of 12,182 by trust here, #1,254 by citations
- Management Science and Operations Research — 80 citations into it; #2,572 of 11,946 by trust here, #3,457 by citations
- Statistics and Probability — 15 citations into it
- Information Systems — 11 citations into it
- Evaluation & Benchmarks — 10 citations into it
- Optimization & Training — 9 citations into it
- Mechanical Engineering — 5 citations into it
Whom Ye Tian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kalyanmoy Deb
- Ran Cheng
- Eckart Zitzler
- Yaochu Jin
- Qingfu Zhang
- Xing-yi Zhang
- Philip Hingston
- Simon Huband
- Hui Li
- Lothar Thiele
Who trusts Ye Tian overall
- Xing-yi Zhang
- Yaochu Jin
- Ran Cheng
- Jing J. Liang
- Xiutao Zheng
- Linqiang Pan
- Yanan Sun
- Hangyu Zhu
- Kaiwen Li
- Xuanxuan Ban
Papers from Ye Tian's perspective
Ordered by how strongly the researchers Ye Tian trusts endorse each paper. Same corpus, a different order for every researcher.
- A fast and elitist multiobjective genetic algorithm: NSGA-II
- Multi-objective optimization using evolutionary algorithms
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
- A review of multiobjective test problems and a scalable test problem toolkit (IEEE Transactions on Evolutionary Computation)
- Gradient-based learning applied to document recognition
- MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition (IEEE Transactions on Evolutionary Computation)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- GENERATIVE ADVERSARIAL NETS
Their papers
- A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization (2015) — 766 citations
- An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization (2015) — 431 citations
- A Decision Variable Clustering-Based Evolutionary Algorithm for Large-Scale Many-Objective Optimization (2018) — 553 citations
- PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum] (2017) — 2,245 citations
- An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility (2018) — 597 citations
- A benchmark test suite for evolutionary many-objective optimization (2017) — 432 citations
- A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization (2019) — 302 citations
- Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multiobjective Optimization (2021) — 305 citations
- A Coevolutionary Framework for Constrained Multiobjective Optimization Problems (2021) — 592 citations
- Evolutionary Large-Scale Multi-Objective Optimization: A Survey (2021) — 426 citations
- Efficient Large-Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer (2020) — 398 citations
- An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization Problems (2020) — 353 citations
- A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization (2018) — 321 citations