Genetic Programming Bibliography entries for Ying Bi

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GP coauthors/coeditors: Harith Al-Sahaf, Qi Chen, Andrew Lensen, Yi Mei, Yanan Sun, Binh Tran, Bing Xue, Mengjie Zhang,

Genetic Programming Articles by Ying Bi

  1. Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming with Image-Related Operators and A Flexible Program Structure for Feature Learning in Image Classification. IEEE Transactions on Evolutionary Computation, 25(1):87-101, 2021. details

  2. Ying Bi and Bing Xue and Mengjie Zhang. An Effective Feature Learning Approach Using Genetic Programming With Image Descriptors for Image Classification [Research Frontier]. IEEE Computational Intelligence Magazine, 15(2):65-77, 2020. details

  3. Harith Al-Sahaf and Ying Bi and Qi Chen and Andrew Lensen and Yi Mei and Yanan Sun and Binh Tran and Bing Xue and Mengjie Zhang. A survey on evolutionary machine learning. Journal of the Royal Society of New Zealand, 49(2):205-228, 2019. The 2019 Annual Collection of Reviews. details

  4. Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming With a New Representation to Automatically Learn Features and Evolve Ensembles for Image Classification. IEEE Transactions on Cybernetics. details

Genetic Programming conference papers by Ying Bi

  1. Ying Bi and Bing Xue and Mengjie Zhang. Evolving Deep Forest with Automatic Feature Extraction for Image Classification Using Genetic Programming. In Thomas Baeck and Mike Preuss and Andre Deutz and Hao Wang2 and Carola Doerr and Michael Emmerich and Heike Trautmann editors, 16th International Conference on Parallel Problem Solving from Nature, Part I, volume 12269, pages 3-18, Leiden, Holland, 2020. Springer. details

  2. Ying Bi and Bing Xue and Mengjie Zhang. Automatically Extracting Features for Face Classification Using Multi-Objective Genetic Programming. 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 117-118, internet, 2020. Association for Computing Machinery. details

  3. Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming-Based Feature Learning for Facial Expression Classification. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24102, internet, 2020. IEEE Press. details

  4. Ying Bi and Bing Xue and Mengjie Zhang. An automated ensemble learning framework using genetic programming for image classification. In Manuel Lopez-Ibanez and Thomas Stuetzle and Anne Auger and Petr Posik and Leslie Peprez Caceres and Andrew M. Sutton and Nadarajen Veerapen and Christine Solnon and Andries Engelbrecht and Stephane Doncieux and Sebastian Risi and Penousal Machado and Vanessa Volz and Christian Blum and Francisco Chicano and Bing Xue and Jean-Baptiste Mouret and Arnaud Liefooghe and Jonathan Fieldsend and Jose Antonio Lozano and Dirk Arnold and Gabriela Ochoa and Tian-Li Yu and Holger Hoos and Yaochu Jin and Ting Hu and Miguel Nicolau and Robin Purshouse and Thomas Baeck and Justyna Petke and Giuliano Antoniol and Johannes Lengler and Per Kristian Lehre editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference, pages 365-373, Prague, Czech Republic, 2019. ACM. details

  5. Ying Bi and Bing Xue and Mengjie Zhang. An Evolutionary Deep Learning Approach Using Genetic Programming with Convolution Operators for Image Classification. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 3197-3204, Wellington, New Zealand, 2019. IEEE Press. details

  6. Ying Bi and Bing Xue and Mengjie Zhang. A Gaussian Filter-Based Feature Learning Approach Using Genetic Programming to Image Classification. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, pages 251-257, Wellington, New Zealand, 2018. Springer. details

  7. Ying Bi and Bing Xue and Mengjie Zhang. An Automatic Feature Extraction Approach to Image Classification Using Genetic Programming. In Stefano Cagnoni and Mengjie Zhang editors, 21st International Conference on the Applications of Evolutionary Computation, EvoIASP 2018, volume 10784, pages 421-438, Parma, Italy, 2018. Springer. details

  8. Ying Bi and Mengjie Zhang and Bing Xue. Genetic Programming for Automatic Global and Local Feature Extraction to Image Classification. In Marley Vellasco editor, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, 2018. IEEE. details

  9. Ying Bi and Mengjie Zhang and Bing Xue. An automatic region detection and processing approach in genetic programming for binary image classification. In 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017. details