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2010 – 2019
- 2013
[c9]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima:
Learning from multiple data sets with different missing attributes and privacy policies: Parallel distributed fuzzy genetics-based machine learning approach. IEEE BigData 2013: 63-70- [c8]Hisao Ishibuchi, Masakazu Yamane, Naoya Akedo, Yusuke Nojima:
Many-objective and many-variable test problems for visual examination of multiobjective search. IEEE Congress on Evolutionary Computation 2013: 1491-1498 - [c7]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Effects of duplicated objectives in many-objective optimization problems on the search behavior of hypervolume-based evolutionary algorithms. MCDM 2013: 25-32 - [c6]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Difficulty in Evolutionary Multiobjective Optimization of Discrete Objective Functions with Different Granularities. EMO 2013: 230-245 - [c5]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Rule weight update in parallel distributed fuzzy genetics-based machine learning with data rotation. FUZZ-IEEE 2013: 1-8 - 2012
- [c4]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Effects of discrete objective functions with different granularities on the search behavior of EMO algorithms. GECCO 2012: 481-488 - [c3]Masakazu Yamane, Akihito Ueda, Naoshi Tadokoro, Yusuke Nojima, Hisao Ishibuchi:
Comparison of different fitness functions in genetic fuzzy rule selection. SCIS&ISIS 2012: 1046-1051 - [c2]Hisao Ishibuchi, Masakazu Yamane, Naoya Akedo, Yusuke Nojima:
Two-objective solution set optimization to maximize hypervolume and decision space diversity in multiobjective optimization. SCIS&ISIS 2012: 1871-1876 - [c1]Hisao Ishibuchi, Masakazu Yamane, Yusuke Nojima:
Ensemble Fuzzy Rule-Based Classifier Design by Parallel Distributed Fuzzy GBML Algorithms. SEAL 2012: 93-103
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