The SCEAS System
Navigation Menu

Search the dblp DataBase

Title:
Author:

Bernhard Sendhoff: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Bernhard Sendhoff, Martin Kreutz
    Analysis of Possible Genome-Dependence of Mutation Rates in Genetic Algorithms. [Citation Graph (0, 0)][DBLP]
    Evolutionary Computing, AISB Workshop, 1996, pp:257-268 [Conf]
  2. Yaochu Jin, Tatsuya Okabe, Bernhard Sendhoff
    Adapting Weighted Aggregation for Multiobjective Evolution Strategies. [Citation Graph (0, 0)][DBLP]
    EMO, 2001, pp:96-110 [Conf]
  3. 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]
  4. 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]
  5. 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]
  6. 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]
  7. Christian Igel, Bernhard Sendhoff
    Synergies between Evolutionary and Neural Computation. [Citation Graph (0, 0)][DBLP]
    ESANN, 2005, pp:241-252 [Conf]
  8. 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]
  9. Martina Hasenjäger, Bernhard Sendhoff, Toyotaka Sonoda, Toshiyuki Arima
    Three dimensional evolutionary aerodynamic design optimization with CMA-ES. [Citation Graph (0, 0)][DBLP]
    GECCO, 2005, pp:2173-2180 [Conf]
  10. 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]
  11. Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
    On Evolutionary Optimization with Approximate Fitness Functions. [Citation Graph (0, 0)][DBLP]
    GECCO, 2000, pp:786-793 [Conf]
  12. 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]
  13. Yaochu Jin, Bernhard Sendhoff
    Incorporation Of Fuzzy Preferences Into Evolutionary Multiobjective Optimization. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:683- [Conf]
  14. Yaochu Jin, Bernhard Sendhoff
    Fitness Approximation In Evolutionary Computation - a Survey. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:1105-1112 [Conf]
  15. Michael Nashvili, Markus Olhofer, Bernhard Sendhoff
    Morphing methods in evolutionary design optimization. [Citation Graph (0, 0)][DBLP]
    GECCO, 2005, pp:897-904 [Conf]
  16. 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]
  17. Peter Stagge, Bernhard Sendhoff
    An Extended Elman Net for Modeling Time Series. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:427-432 [Conf]
  18. Bernhard Sendhoff, Martin Kreutz, Werner von Seelen
    A Condition for the Genotype-Phenotype Mapping: Causality. [Citation Graph (0, 0)][DBLP]
    ICGA, 1997, pp:73-80 [Conf]
  19. 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]
  20. Hee-Khiang Ng, Dudy Lim, Yew-Soon Ong, Bu-Sung Lee, Lars Freund, Shuja Parvez, Bernhard Sendhoff
    A Multi-cluster Grid Enabled Evolution Framework for Aerodynamic Airfoil Design Optimization. [Citation Graph (0, 0)][DBLP]
    ICNC (2), 2005, pp:1112-1121 [Conf]
  21. Razvan Enache, Bernhard Sendhoff, Markus Olhofer, Martina Hasenjäger
    Comparison of Steady-State and Generational Evolution Strategies for Parallel Architectures. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:253-262 [Conf]
  22. Vineet R. Khare, Bernhard Sendhoff, Xin Yao
    Environments Conducive to Evolution of Modularity. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:603-612 [Conf]
  23. Vineet R. Khare, Xin Yao, Bernhard Sendhoff
    Credit Assignment Among Neurons in Co-evolving Populations. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:882-891 [Conf]
  24. Martin Kreutz, Anja M. Reimetz, Bernhard Sendhoff, Claus Weihs, Werner von Seelen
    Optimisation of Density Estimation Models with Evolutionary Algorithms. [Citation Graph (0, 0)][DBLP]
    PPSN, 1998, pp:998-1007 [Conf]
  25. 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]
  26. Stefan Menzel, Markus Olhofer, Bernhard Sendhoff
    Direct Manipulation of Free Form Deformation in Evolutionary Design Optimisation. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:352-361 [Conf]
  27. Georg Schneider, Heiko Wersing, Bernhard Sendhoff, Edgar Körner
    Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:662-671 [Conf]
  28. 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]
  29. 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]
  30. Hans-Georg Beyer, Markus Olhofer, Bernhard Sendhoff
    On the Impact of Systematic Noise on the Evolutionary Optimization Performance-A Sphere Model Analysis. [Citation Graph (0, 0)][DBLP]
    Genetic Programming and Evolvable Machines, 2004, v:5, n:4, pp:327-360 [Journal]
  31. 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]
  32. 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]
  33. 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]
  34. Bernhard Sendhoff, Martin Kreutz
    A Model for the Dynamic Interaction Between Evolution and Learning. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1999, v:10, n:3, pp:181-193 [Journal]
  35. 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]
  36. 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]
  37. Hans-Georg Beyer, Bernhard Sendhoff
    Functions with noise-induced multimodality: a test for evolutionary robust Optimization-properties and performance analysis. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2006, v:10, n:5, pp:507-526 [Journal]
  38. 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]
  39. Georg Schneider, Heiko Wersing, Bernhard Sendhoff, Edgar Körner
    Evolutionary optimization of a hierarchical object recognition model. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part B, 2005, v:35, n:3, pp:426-437 [Journal]
  40. Ingo Paenke, Bernhard Sendhoff, Jon Rowe, Chrisantha Fernando
    On the Adaptive Disadvantage of Lamarckianism in Rapidly Changing Environments. [Citation Graph (0, 0)][DBLP]
    ECAL, 2007, pp:355-364 [Conf]
  41. 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]
  42. 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]
  43. 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]
  44. Hans-Georg Beyer, Bernhard Sendhoff
    Evolutionary Algorithms in the Presence of Noise: To Sample or Not to Sample. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:17-24 [Conf]
  45. 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]
  46. 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]
  47. Martina Hasenjäger, Bernhard Sendhoff
    Crawling along the Pareto front: tales from the practice. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:174-181 [Conf]
  48. 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]

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


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


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


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


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


  54. Knowledge Extraction from Unstructured Surface Meshes. [Citation Graph (, )][DBLP]


  55. Interaction Detection in Aerodynamic Design Data. [Citation Graph (, )][DBLP]


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


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


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


  59. Word Recognition with a Hierarchical Neural Network. [Citation Graph (, )][DBLP]


  60. Covariance Matrix Adaptation Revisited - The CMSA Evolution Strategy -. [Citation Graph (, )][DBLP]


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


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


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


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


  65. Target shape design optimization by evolving splines. [Citation Graph (, )][DBLP]


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


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


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


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


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


  71. The Influence of Learning on Evolution: A Mathematical Framework. [Citation Graph (, )][DBLP]


Search in 0.094secs, Finished in 0.096secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002