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Publication search results
found 64 matches
- 2023
- Fursan Thabit, Özgü Can, Rizwan Uz Zaman Wani, Mohammed Ali Qasem, S. B. Thorat, Hoda A. AlKhzaimi:
Data security techniques in cloud computing based on machine learning algorithms and cryptographic algorithms: Lightweight algorithms and genetics algorithms. Concurr. Comput. Pract. Exp. 35(21) (2023) - Meiling Wang, Wei Shao, Shuo Huang, Daoqiang Zhang:
Hypergraph-regularized multimodal learning by graph diffusion for imaging genetics based Alzheimer's Disease diagnosis. Medical Image Anal. 89: 102883 (2023) - 2022
- Mansu Kim, Eun Jeong Min, Kefei Liu, Jingwen Yan, Andrew J. Saykin, Jason H. Moore, Qi Long, Li Shen:
Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. Medical Image Anal. 76: 102297 (2022) - Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Evolutionary Multi-Objective Multi-Tasking for Fuzzy Genetics-Based Machine Learning in Multi-Label Classification. FUZZ-IEEE 2022: 1-8 - Takeru Konishi, Naoki Masuyama, Yusuke Nojima:
Effects of Accuracy-based Single-Objective Optimization in Multiobjective Fuzzy Genetics-based Machine Learning. SCIS/ISIS 2022: 1-6 - 2020
- Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Multiobjective Fuzzy Genetics-Based Machine Learning for Multi-Label Classification. FUZZ-IEEE 2020: 1-8 - 2018
- Chi Yang, Chun-Hui Jen, Chun-Yen Chang, Ting-Kuang Yeh:
Comparison of Animation and Static-picture based Instruction: Effects on Performance and Cognitive Load for Learning Genetics. J. Educ. Technol. Soc. 21(4): 1-11 (2018) - 2017
- Yusuke Nojima, Koki Arahari, Shuji Takemura, Hisao Ishibuchi:
Multiobjective fuzzy genetics-based machine learning based on MOEA/D with its modifications. FUZZ-IEEE 2017: 1-6 - Genetics-Based Machine Learning. Encyclopedia of Machine Learning and Data Mining 2017: 568
- 2016
- Yusuke Nojima, Hisao Ishibuchi:
Effects of parallel distributed implementation on the search performance of Pittsburgh-style genetics-based machine learning algorithms. CEC 2016: 2193-2200 - Yusuke Nojima, Hisao Ishibuchi:
Multiobjective fuzzy genetics-based machine learning with a reject option. FUZZ-IEEE 2016: 1405-1412 - Jailin Peng, Le An, Xiaofeng Zhu, Yan Jin, Dinggang Shen:
Structured Sparse Kernel Learning for Imaging Genetics Based Alzheimer's Disease Diagnosis. MICCAI (2) 2016: 70-78 - Anurag Deep, Sahana Murthy, Paike Jayadeva Bhat:
Geneticus Investigation: An Agent-Based Modeling System for Teaching-Learning Hypothetico-Deductive Reasoning in Mendelian genetics. T4E 2016: 164-171 - 2015
- Yusuke Nojima, Yuji Takahashi, Hisao Ishibuchi:
Application of Parallel Distributed Implementation to Multiobjective Fuzzy Genetics-Based Machine Learning. ACIIDS (1) 2015: 462-471 - Yuji Takahashi, Yusuke Nojima, Hisao Ishibuchi:
Rotation effects of objective functions in parallel distributed multiobjective fuzzy genetics-based machine learning. ASCC 2015: 1-6 - Yusuke Nojima, Kazuhiro Watanabe, Hisao Ishibuchi:
Effects of heuristic rule generation from multiple patterns in multiobjective fuzzy genetics-Based machine learning. CEC 2015: 2996-3003 - Yusuke Nojima, Kazuhiro Watanabe, Hisao Ishibuchi:
Simple modifications on heuristic rule generation and rule evaluation in Michigan-style fuzzy genetics-based machine learning. FUZZ-IEEE 2015: 1-8 - Yusuke Nojima, Kazuhiro Watanabe, Hisao Ishibuchi:
Variants of heuristic rule generation from multiple patterns in Michigan-style fuzzy genetics-based machine learning. TAAI 2015: 427-432 - 2014
- Yohannes Kassahun, Roberta Perrone, Elena De Momi, Elmar Berghöfer, Laura Tassi, Maria Paola Canevini, Roberto Spreafico, Giancarlo Ferrigno, Frank Kirchner:
Automatic classification of epilepsy types using ontology-based and genetics-based machine learning. Artif. Intell. Medicine 61(2): 79-88 (2014) - Yuji Takahashi, Yusuke Nojima, Hisao Ishibuchi:
Hybrid fuzzy genetics-based machine learning with entropy-based inhomogeneous interval discretization. FUZZ-IEEE 2014: 1512-1517 - Yusuke Nojima, Yuji Takahashi, Hisao Ishibuchi:
Genetic lateral tuning of membership functions as post-processing for hybrid fuzzy genetics-based machine learning. SCIS&ISIS 2014: 667-672 - 2013
- María A. Franco, Natalio Krasnogor, Jaume Bacardit:
GAssist vs. BioHEL: critical assessment of two paradigms of genetics-based machine learning. Soft Comput. 17(6): 953-981 (2013) - Jaume Bacardit, Xavier Llorà:
Large-scale data mining using genetics-based machine learning. WIREs Data Mining Knowl. Discov. 3(1): 37-61 (2013) - 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 - 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 - Jaume Bacardit, Xavier Llorà:
Large scale data mining using genetics-based machine learning. GECCO (Companion) 2013: 741-764 - Hisao Ishibuchi, Yusuke Nojima:
Difficulties in choosing a single final classifier from non-dominated solutions in multiobjective fuzzy genetics-based machine learning. IFSA/NAFIPS 2013: 1203-1208 - 2012
- Yusuke Nojima, Shingo Mihara, Hisao Ishibuchi:
Application of parallel distributed genetics-based machine learning to imbalanced data sets. FUZZ-IEEE 2012: 1-6 - Jaume Bacardit, Xavier Llorà:
Large scale data mining using genetics-based machine learning. GECCO (Companion) 2012: 1171-1196 - Tim Kovacs:
Genetics-Based Machine Learning. Handbook of Natural Computing 2012: 937-986
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