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Yaochu Jin: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Yaochu Jin, Tatsuya Okabe, Bernhard Sendhoff
    Adapting Weighted Aggregation for Multiobjective Evolution Strategies. [Citation Graph (0, 0)][DBLP]
    EMO, 2001, pp:96-110 [Conf]
  2. Yaochu Jin, Bernhard Sendhoff
    Trade-Off between Performance and Robustness: An Evolutionary Multiobjective Approach. [Citation Graph (0, 0)][DBLP]
    EMO, 2003, pp:237-251 [Conf]
  3. Yaochu Jin, Bernhard Sendhoff, Edgar Körner
    Evolutionary Multi-objective Optimization for Simultaneous Generation of Signal-Type and Symbol-Type Representations. [Citation Graph (0, 0)][DBLP]
    EMO, 2005, pp:752-766 [Conf]
  4. Aimin Zhou, Yaochu Jin, Qingfu Zhang, Bernhard Sendhoff, Edward P. K. Tsang
    Prediction-Based Population Re-initialization for Evolutionary Dynamic Multi-objective Optimization. [Citation Graph (0, 0)][DBLP]
    EMO, 2006, pp:832-846 [Conf]
  5. Lars Gräning, Yaochu Jin, Bernhard Sendhoff
    Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study. [Citation Graph (0, 0)][DBLP]
    ESANN, 2005, pp:273-278 [Conf]
  6. Yaochu Jin, Bernhard Sendhoff
    Constructing Dynamic Optimization Test Problems Using the Multi-objective Optimization Concept. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2004, pp:525-536 [Conf]
  7. Yaochu Jin, Bernhard Sendhoff
    Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles. [Citation Graph (0, 0)][DBLP]
    GECCO (1), 2004, pp:688-699 [Conf]
  8. Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
    On Evolutionary Optimization with Approximate Fitness Functions. [Citation Graph (0, 0)][DBLP]
    GECCO, 2000, pp:786-793 [Conf]
  9. Yaochu Jin, Tatsuya Okabe, Bernhard Sendhoff
    Solving Three-Objective Optimization Problems Using Evolutionary Dynamic Weighted Aggregation: Results and Analysis. [Citation Graph (0, 0)][DBLP]
    GECCO, 2003, pp:636-637 [Conf]
  10. Yaochu Jin, Bernhard Sendhoff
    Incorporation Of Fuzzy Preferences Into Evolutionary Multiobjective Optimization. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:683- [Conf]
  11. Yaochu Jin, Bernhard Sendhoff
    Fitness Approximation In Evolutionary Computation - a Survey. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:1105-1112 [Conf]
  12. Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff
    On The Dynamics Of Evolutionary Multi-objective Optimization. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:247-256 [Conf]
  13. Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
    On Evolutionary Optimization of Large Problems Using Small Populations. [Citation Graph (0, 0)][DBLP]
    ICNC (2), 2005, pp:1145-1154 [Conf]
  14. Tatsuya Okabe, Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
    On Test Functions for Evolutionary Multi-objective Optimization. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:792-802 [Conf]
  15. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff, Edward P. K. Tsang
    Modelling the Population Distribution in Multi-objective Optimization by Generative Topographic Mapping. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:443-452 [Conf]
  16. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee
    Efficient Hierarchical Parallel Genetic Algorithms using Grid computing. [Citation Graph (0, 0)][DBLP]
    Future Generation Comp. Syst., 2007, v:23, n:4, pp:658-670 [Journal]
  17. Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei, Kim-Fung Man
    Multi-objective hierarchical genetic algorithm for interpretable fuzzy rule-based knowledge extraction. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2005, v:149, n:1, pp:149-186 [Journal]
  18. Shengxiang Yang, Yew-Soon Ong, Yaochu Jin
    Editorial to special issue on evolutionary computation in dynamic and uncertain environments. [Citation Graph (0, 0)][DBLP]
    Genetic Programming and Evolvable Machines, 2006, v:7, n:4, pp:293-294 [Journal]
  19. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee
    Inverse multi-objective robust evolutionary design. [Citation Graph (0, 0)][DBLP]
    Genetic Programming and Evolvable Machines, 2006, v:7, n:4, pp:383-404 [Journal]
  20. Yaochu Jin, Bernhard Sendhoff
    Extracting Interpretable Fuzzy Rules from RBF Networks. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2003, v:17, n:2, pp:149-164 [Journal]
  21. Yaochu Jin, Bernhard Sendhoff
    Knowledge Incorporation into Neural Networks From Fuzzy Rules. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1999, v:10, n:3, pp:231-242 [Journal]
  22. Michael Hüsken, Yaochu Jin, Bernhard Sendhoff
    Structure optimization of neural networks for evolutionary design optimization. [Citation Graph (0, 0)][DBLP]
    Soft Comput., 2005, v:9, n:1, pp:21-28 [Journal]
  23. Yaochu Jin
    A comprehensive survey of fitness approximation in evolutionary computation. [Citation Graph (0, 0)][DBLP]
    Soft Comput., 2005, v:9, n:1, pp:3-12 [Journal]
  24. Yaochu Jin, Sushil J. Louis, Khaled Rasheed
    Guest Editorial. [Citation Graph (0, 0)][DBLP]
    Soft Comput., 2005, v:9, n:1, pp:1-2 [Journal]
  25. Yaochu Jin, Jürgen Branke
    Evolutionary optimization in uncertain environments-a survey. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2005, v:9, n:3, pp:303-317 [Journal]
  26. Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
    A framework for evolutionary optimization with approximate fitness functions. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2002, v:6, n:5, pp:481-494 [Journal]
  27. Ingo Paenke, Jürgen Branke, Yaochu Jin
    Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2006, v:10, n:4, pp:405-420 [Journal]
  28. Yaochu Jin
    Decentralized adaptive fuzzy control of robot manipulators. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part B, 1998, v:28, n:1, pp:47-57 [Journal]
  29. Yaochu Jin, Werner von Seelen, Bernhard Sendhoff
    On generating FC3 fuzzy rule systems from data using evolution strategies. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part B, 1999, v:29, n:6, pp:829-845 [Journal]
  30. Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei, Kim-Fung Man
    Agent-based evolutionary approach for interpretable rule-based knowledge extraction. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part C, 2005, v:35, n:2, pp:143-155 [Journal]
  31. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff, Edward P. K. Tsang
    Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover. [Citation Graph (0, 0)][DBLP]
    GECCO, 2007, pp:617-623 [Conf]
  32. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff
    A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation. [Citation Graph (0, 0)][DBLP]
    GECCO, 2007, pp:1288-1295 [Conf]
  33. Yaochu Jin, Ruojing Wen, Bernhard Sendhoff
    Evolutionary Multi-objective Optimization of Spiking Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:370-379 [Conf]
  34. Ingo Paenke, Jürgen Branke, Yaochu Jin
    On the Influence of Phenotype Plasticity on Genotype Diversity. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:33-40 [Conf]
  35. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Edward P. K. Tsang, Tatsuya Okabe
    A model-based evolutionary algorithm for bi-objective optimization. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:2568-2575 [Conf]
  36. Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff
    Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:382-389 [Conf]
  37. Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff
    A new approach to dynamics analysis of genetic algorithms without selection. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:374-381 [Conf]
  38. Vineet R. Khare, Xin Yao, Bernhard Sendhoff, Yaochu Jin, Heiko Wersing
    Co-evolutionary modular neural networks for automatic problem decomposition. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:2691-2698 [Conf]

  39. Real-World Applications of Multiobjective Optimization. [Citation Graph (, )][DBLP]


  40. A cellular model for the evolutionary development of lightweight material with an inner structure. [Citation Graph (, )][DBLP]


  41. NEATfields: evolution of neural fields. [Citation Graph (, )][DBLP]


  42. Evolving heterochrony for cellular differentiation using vector field embryogeny. [Citation Graph (, )][DBLP]


  43. Pareto-based Multi-Objective Machine Learning. [Citation Graph (, )][DBLP]


  44. Evolutionary Optimization with Dynamic Fidelity Computational Models. [Citation Graph (, )][DBLP]


  45. A Gene Regulatory Model for the Development of Primitive Nervous Systems. [Citation Graph (, )][DBLP]


  46. Evolution of Neural Organization in a Hydra-Like Animat. [Citation Graph (, )][DBLP]


  47. Generalization Improvement in Multi-Objective Learning. [Citation Graph (, )][DBLP]


  48. Alleviating Catastrophic Forgetting via Multi-Objective Learning. [Citation Graph (, )][DBLP]


  49. Prediction of convergence dynamics of design performance using differential recurrent neural networks. [Citation Graph (, )][DBLP]


  50. Emergent Distribution of Computational Workload in the Evolution of an Undulatory Animat. [Citation Graph (, )][DBLP]


  51. Robustness Analysis and Failure Recovery of a Bio-Inspired Self-Organizing Multi-Robot System. [Citation Graph (, )][DBLP]


  52. Comparing neural networks and Kriging for fitness approximation in evolutionary optimization. [Citation Graph (, )][DBLP]


  53. Comparative studies on micro heat exchanger optimisation. [Citation Graph (, )][DBLP]


  54. Adaptivemodelling strategy for continuous multi-objective optimization. [Citation Graph (, )][DBLP]


  55. Emergence of feedback in artificial gene regulatory networks. [Citation Graph (, )][DBLP]


  56. Toward a gene regulatory network model for evolving chemotaxis behavior. [Citation Graph (, )][DBLP]


  57. Evolving in silico bistable and oscillatory dynamics for gene regulatory network motifs. [Citation Graph (, )][DBLP]


  58. Combination of EDA and DE for continuous biobjective optimization. [Citation Graph (, )][DBLP]


  59. Global shape with morphogen gradients and motile polarized cells. [Citation Graph (, )][DBLP]


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