Genetic Programming Bibliography entries for Lin Shang

up to index Created by W.Langdon from gp-bibliography.bib Revision:1.7964

GP coauthors/coeditors: Jiatong Huo, Bing Xue, Mengjie Zhang, Yiming Li, Mingqian Lin, Xiaoying (Sharon) Gao, Zeyu Mi, Wenbin Pei, Cheng Xie,

Genetic Programming Articles by Lin Shang

  1. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Detecting Overlapping Areas in Unbalanced High-dimensional Data Using Neighborhood Rough Set and Genetic Programming. IEEE Transactions on Evolutionary Computation, 27(4):1130-1144, 2023. details

  2. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. High-dimensional Unbalanced Binary Classification by Genetic Programming with Multi-criterion Fitness Evaluation and Selection. Evolutionary Computation, 30(1):99-129, 2022. details

  3. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Developing Interval-Based Cost-Sensitive Classifiers by Genetic Programming for Binary High-Dimensional Unbalanced Classification [Research Frontier]. IEEE Computational Intelligence Magazine, 16(1):84-98, 2021. details

  4. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Genetic programming for development of cost-sensitive classifiers for binary high-dimensional unbalanced classification. Applied Soft Computing, 101:106989, 2021. details

  5. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Genetic programming for high-dimensional imbalanced classification with a new fitness function and program reuse mechanism. Soft Computing, 24(23):18021-18038, 2020. Special Issue Dedicated to the 3rd International Conference "Numerical Computations: Theory and Algorithms, NUMTA 2019" June 15-21, 2019, Isola Capo Rizzuto, Italy. details

Genetic Programming conference papers by Lin Shang

  1. Mingqian Lin and Lin Shang and Xiaoying Gao. Enhancing Interpretability in AI-Generated Image Detection with Genetic Programming. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW), pages 371-378, 2023. details

  2. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Genetic Programming for Borderline Instance Detection in High-dimensional Unbalanced Classification. In Francisco Chicano and Alberto Tonda and Krzysztof Krawiec and Marde Helbig and Christopher W. Cleghorn and Dennis G. Wilson and Georgios Yannakakis and Luis Paquete and Gabriela Ochoa and Jaume Bacardit and Christian Gagne and Sanaz Mostaghim and Laetitia Jourdan and Oliver Schuetze and Petr Posik and Carlos Segura and Renato Tinos and Carlos Cotta and Malcolm Heywood and Mengjie Zhang and Leonardo Trujillo and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Fuyuki Ishikawa and Inmaculada Medina-Bulo and Frank Neumann and Andrew M. Sutton editors, Proceedings of the 2021 Genetic and Evolutionary Computation Conference, pages 349-357, internet, 2021. Association for Computing Machinery. details

  3. Yiming Li and Lin Shang. Re-ID BUFF: An Enhanced Similarity Measurement Based on Genetic Programming for Person Re-identification. In Francisco Chicano and Alberto Tonda and Krzysztof Krawiec and Marde Helbig and Christopher W. Cleghorn and Dennis G. Wilson and Georgios Yannakakis and Luis Paquete and Gabriela Ochoa and Jaume Bacardit and Christian Gagne and Sanaz Mostaghim and Laetitia Jourdan and Oliver Schuetze and Petr Posik and Carlos Segura and Renato Tinos and Carlos Cotta and Malcolm Heywood and Mengjie Zhang and Leonardo Trujillo and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Fuyuki Ishikawa and Inmaculada Medina-Bulo and Frank Neumann and Andrew M. Sutton editors, Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion, pages 255-256, internet, 2021. Association for Computing Machinery. details

  4. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. A Genetic Programming Method for Classifier Construction and Cost Learning in High-Dimensional Unbalanced Classification. In Richard Allmendinger and Hugo Terashima Marin and Efren Mezura Montes and Thomas Bartz-Beielstein and Bogdan Filipic and Ke Tang and David Howard and Emma Hart and Gusz Eiben and Tome Eftimov and William La Cava and Boris Naujoks and Pietro Oliveto and Vanessa Volz and Thomas Weise and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Rui Wang and Ran Cheng and Guohua Wu and Miqing Li and Hisao Ishibuchi and Jonathan Fieldsend and Ozgur Akman and Khulood Alyahya and Juergen Branke and John R. Woodward and Daniel R. Tauritz and Marco Baioletti and Josu Ceberio Uribe and John McCall and Alfredo Milani and Stefan Wagner and Michael Affenzeller and Bradley Alexander and Alexander (Sandy) Brownlee and Saemundur O. Haraldsson and Markus Wagner and Nayat Sanchez-Pi and Luis Marti and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and Matthew Johns and Nick Ross and Ed Keedwell and Herman Mahmoud and David Walker and Anthony Stein and Masaya Nakata and David Paetzel and Neil Vaughan and Stephen Smith and Stefano Cagnoni and Robert M. Patton and Ivanoe De Falco and Antonio Della Cioppa and Umberto Scafuri and Ernesto Tarantino and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Erik Hemberg and Riyad Alshammari and Tokunbo Makanju and Fuijimino-shi and Ivan Zelinka and Swagatam Das and Ponnuthurai Nagaratnam and Roman Senkerik editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pages 149-150, internet, 2020. Association for Computing Machinery. details

  5. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. A Threshold-free Classification Mechanism in Genetic Programming for High-dimensional Unbalanced Classification. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24341, internet, 2020. IEEE Press. details

  6. Wenbin Pei and Bing Xue and Mengjie Zhang and Lin Shang. A Cost-sensitive Genetic Programming Approach for High-dimensional Unbalanced Classification. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1770-1777, 2019. details

  7. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Reuse of program trees in genetic programming with a new fitness function in high-dimensional unbalanced classification. In Richard Allmendinger and Carlos Cotta and Carola Doerr and Pietro S. Oliveto and Thomas Weise and Ales Zamuda and Anne Auger and Dimo Brockhoff and Nikolaus Hansen and Tea Tusar and Konstantinos Varelas and David Camacho-Fernandez and Massimiliano Vasile and Annalisa Riccardi and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Ozgur Akman and Khulood Alyahya and Juergen Branke and Jonathan Fieldsend and Tinkle Chugh and Jussi Hakanen and Josu Ceberio Uribe and Valentino Santucci and Marco Baioletti and John McCall and Emma Hart and Daniel R. Tauritz and John R. Woodward and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Eneko Osaba and Javier Del Ser and Pascal Kerschke and Boris Naujoks and Vanessa Volz and Anna I Esparcia-Alcazar and Riyad Alshammari and Erik Hemberg and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Walker and Matt Johns and Nick Ross and Ed Keedwell and Masaya Nakata and Anthony Stein and Takato Tatsumi and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Marcus Gallagher and Mike Preuss and Olivier Teytaud and Fernando Lezama and Joao Soares and Zita Vale editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 187-188, Prague, Czech Republic, 2019. ACM. details

  8. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. New Fitness Functions in Genetic Programming for Classification with High-dimensional Unbalanced Data. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 2779-2786, Wellington, New Zealand, 2019. IEEE Press. details

  9. Zeyu Mi and Lin Shang and Bing Xue. Multi-Dimensional Optical Flow Embedded Genetic Programming for Anomaly Detection in Crowded Scenes. In Long Cheng and Andrew Chi Sing Leung and Seiichi Ozawa editors, Proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, volume 11301, Siem Reap, Cambodia, 2018. Springer. details

  10. Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang. Genetic Programming Based on Granular Computing for Classification with High-Dimensional Data. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, pages 643-655, Wellington, New Zealand, 2018. Springer. details

  11. Jiatong Huo and Bing Xue and Lin Shang and Mengjie Zhang. Genetic Programming for Multi-objective Test Data Generation in Search Based Software Testing. In Wei Peng and Damminda Alahakoon and Xiaodong Li editors, AI 2017: Advances in Artificial Intelligence - 30th Australasian Joint Conference, Melbourne, VIC, Australia, August 19-20, 2017, Proceedings, volume 10400, pages 169-181, 2017. Springer. details

  12. Cheng Xie and Lin Shang. Anomaly Detection in Crowded Scenes Using Genetic Programming. In Carlos A. Coello Coello editor, Proceedings of the 2014 IEEE Congress on Evolutionary Computation, pages 1832-1839, Beijing, China, 2014. details