Genetic Programming Bibliography entries for Bing Xue

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GP coauthors/coeditors: Shima Afzali, Harith Al-Sahaf, Christopher Hollitt, Mengjie Zhang, Soha Ahmed, Lifeng Peng, Baligh Al-Helali, Qi Chen, Ying Bi, Andrew Lensen, Yi Mei, Yanan Sun, Binh Ngan Tran, Ausama Al-Sahaf, Mark Johnston, Hayden Andersen, Samaneh Azari, Dana Briscoe, Ross Vennell, Pablo Mesejo Santiago, Stefano Cagnoni, Ben Niu, Andrea De Lorenzo, Alberto Bartoli, Mauro Castelli, Eric Medvet, Benjamin Evans, Qinglan Fan, Wenlong Fu, Xiaoying (Sharon) Gao, Edward Haslam, Jiatong Huo, Lin Shang, Muhammad Iqbal, Yi Liu2, Will N Browne, Miao Lu, Qiong Hu, Yanbing Wei, Peng Yang, Wenbin Wu, Abigail McGhie, Gisele L Pappa, Su Nguyen, Zeyu Mi, Brandon Muller, Damien O'Neill, Wenbin Pei, Bo Peng, Shuting Wan, Tessa Phillips, Christian Raymond, Cao Truong Tran, Peter Andreae, Qurrat Ul Ain, Caiyun Wen, Shengnan Zhang, Qingbo Zhou, Xin Yao, Zichu Yan, Yunhan Yang, Linley Jesson,

Genetic Programming Articles by Bing Xue

  1. Caiyun Wen and Miao Lu and Ying Bi and Shengnan Zhang and Bing Xue and Mengjie Zhang and Qingbo Zhou and Wenbin Wu. An Object-Based Genetic Programming Approach for Cropland Field Extraction. Remote Sensing, 14(5) 2022. Special Issue Progresses in Agro-Geoinformatics. 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. Miao Lu and Ying Bi and Bing Xue and Qiong Hu and Mengjie Zhang and Yanbing Wei and Peng Yang and Wenbin Wu. Genetic Programming for High-Level Feature Learning in Crop Classification. Remote Sensing, 14(16):3982, 2022. Special Issue Remote Sensing for Mapping Farmland and Agricultural Infrastructure. details

  4. Andrew Lensen and Bing Xue and Mengjie Zhang. Genetic Programming for Manifold Learning: Preserving Local Topology. IEEE Transactions on Evolutionary Computation, 26(4):661-675, 2022. details

  5. Ying Bi and Bing Xue and Mengjie Zhang. Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning. IEEE Transactions on Evolutionary Computation, 26(2):218-232, 2022. Special Issue on Multitask Evolutionary Computation. details

  6. Qinglan Fan and Ying Bi and Bing Xue and Mengjie Zhang. Genetic programming for feature extraction and construction in image classification. Applied Soft Computing, 118:108509, 2022. details

  7. Ying Bi and Bing Xue and Mengjie Zhang. Dual-Tree Genetic Programming for Few-Shot Image Classification. IEEE Transactions on Evolutionary Computation, 26(3):555-569, 2022. details

  8. Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming for Instance Transfer Learning in Symbolic Regression. IEEE Transactions on Cybernetics, 52(1):25-38, 2022. details

  9. Bo Peng and Ying Bi and Bing Xue and Mengjie Zhang and Shuting Wan. A Survey on Fault Diagnosis of Rolling Bearings. Algorithms, 15:article 347, 2022. Special Issue Artificial Intelligence for Fault Detection and Diagnosis. details

  10. Ying Bi and Bing Xue and Mengjie Zhang. Using a Small Number of Training Instances in Genetic Programming for Face Image Classification. Information Sciences, 593:488-504, 2022. details

  11. Qurrat Ul Ain and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. Generating Knowledge-Guided Discriminative Features Using Genetic Programming for Melanoma Detection. IEEE Transactions on Emerging Topics in Computational Intelligence, 5(4):554-569, 2021. details

  12. Qi Chen and Bing Xue and Mengjie Zhang. Preserving Population Diversity Based on Transformed Semantics in Genetic Programming for Symbolic Regression. IEEE Transactions on Evolutionary Computation, 25(3):433-447, 2021. details

  13. Bo Peng and Shuting Wan and Ying Bi and Bing Xue and Mengjie Zhang. Automatic Feature Extraction and Construction Using Genetic Programming for Rotating Machinery Fault Diagnosis. IEEE Transactions on Cybernetics, 51(10):4909-4923, 2021. details

  14. Bo Peng and Ying Bi and Bing Xue and Mengjie Zhang and Shuting Wan. Multi-View Feature Construction Using Genetic Programming for Rolling Bearing Fault Diagnosis [Application Notes]. IEEE Computational Intelligence Magazine, 16(3):79-94, 2021. details

  15. 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

  16. 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

  17. Andrew Lensen and Bing Xue and Mengjie Zhang. Genetic Programming for Evolving a Front of Interpretable Models for Data Visualization. IEEE Transactions on Cybernetics, 51(11):5468-5482, 2021. details

  18. Wenlong Fu and Bing Xue and Xiaoying Gao and Mengjie Zhang. Output-based transfer learning in genetic programming for document classification. Knowledge-Based Systems, 212:106597, 2021. details

  19. Wenlong Fu and Bing Xue and Xiaoying Gao and Mengjie Zhang. Transductive transfer learning based Genetic Programming for balanced and unbalanced document classification using different types of features. Applied Soft Computing, 103:107172, 2021. details

  20. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. A new imputation method based on genetic programming and weighted KNN for symbolic regression with incomplete data. Soft Computing, 25(8):5993-6012, 2021. details

  21. Ying Bi and Bing Xue and Mengjie Zhang. A Divide-and-Conquer Genetic Programming Algorithm with Ensembles for Image Classification. IEEE Transactions on Evolutionary Computation, 25(6):1148-1162, 2021. details

  22. Ying Bi and Bing Xue and Mengjie Zhang. Multi-objective genetic programming for feature learning in face recognition. Applied Soft Computing, 103:107152, 2021. details

  23. 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

  24. 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, 51(4):1769-1783, 2021. details

  25. Harith Al-Sahaf and Ausama Al-Sahaf and Bing Xue and Mengjie Zhang. Automatically Evolving Texture Image Descriptors using the Multi-tree Representation in Genetic Programming using Few Instances. Evolutionary Computation, 29(3):331-366, 2021. details

  26. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multi-Tree Genetic Programming with New Operators for Transfer Learning in Symbolic Regression with Incomplete Data. IEEE Transactions on Evolutionary Computation, 25(6):1049-1063, 2021. details

  27. Shima Afzali Vahed Moghaddam and Harith Al-Sahaf and Bing Xue and Christopher Hollitt and Mengjie Zhang. An automatic feature construction method for salient object detection: A genetic programming approach. Expert Systems with Applications, 186:115726, 2021. details

  28. 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

  29. Andrew Lensen and Mengjie Zhang and Bing Xue. Multi-objective genetic programming for manifold learning: balancing quality and dimensionality. Genetic Programming and Evolvable Machines, 21(3):399-431, 2020. Special Issue: Highlights of Genetic Programming 2019 Events. details

  30. Andrew Lensen and Bing Xue and Mengjie Zhang. Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis. Evolutionary Computation, 28(4):531-561, 2020. Winter. details

  31. Andrea De Lorenzo and Alberto Bartoli and Mauro Castelli and Eric Medvet and Bing Xue. Genetic programming in the twenty-first century: a bibliometric and content-based analysis from both sides of the fence. Genetic Programming and Evolvable Machines, 21(1-2):181-204, 2020. Twentieth Anniversary Issue. details

  32. 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

  33. Muhammad Iqbal and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. Genetic programming with transfer learning for texture image classification. Soft Computing, 23(23):12859-12871, 2019. details

  34. Binh Tran and Bing Xue and Mengjie Zhang. Genetic programming for multiple-feature construction on high-dimensional classification. Pattern Recognition, 93:404-417, 2019. details

  35. Su Nguyen and Yi Mei and Bing Xue and Mengjie Zhang. A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules. Evolutionary Computation, 27(3):467-496, 2019. details

  36. Qi Chen and Mengjie Zhang and Bing Xue. Structural Risk Minimisation-Driven Genetic Programming for Enhancing Generalisation in Symbolic Regression. IEEE Transactions on Evolutionary Computation, 23(4):703-717, 2019. details

  37. Qi Chen and Bing Xue and Mengjie Zhang. Improving Generalisation of Genetic Programming for Symbolic Regression with Angle-Driven Geometric Semantic Operators. IEEE Transactions on Evolutionary Computation, 23(3):488-502, 2019. details

  38. 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

  39. Ying Bi and Bing Xue and Mengjie Zhang. A Survey on Genetic Programming to Image Analysis. Journal of Zhengzhou University (Engineering Science), 39(6):3-13, 2018. In Chinese. details

  40. Bing Xue. Sebastian Ventura and Jose Maria Luna: Pattern mining with evolutionary algorithms. Genetic Programming and Evolvable Machines, 18(3):407-409, 2017. Book review. details

  41. Bing Xue and Mengjie Zhang. Evolutionary Feature Manipulation in Data Mining/Big Data. SIGEVOlution, 10(1):4-11, 2017. details

  42. Yi Mei and Su Nguyen and Bing Xue and Mengjie Zhang. An Efficient Feature Selection Algorithm for Evolving Job Shop Scheduling Rules With Genetic Programming. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(5):339-353, 2017. details

  43. Muhammad Iqbal and Bing Xue and Harith Al-Sahaf and Mengjie Zhang. Cross-Domain Reuse of Extracted Knowledge in Genetic Programming for Image Classification. IEEE Transactions on Evolutionary Computation, 21(4):569-587, 2017. details

  44. Qi Chen and Mengjie Zhang and Bing Xue. Feature Selection to Improve Generalisation of Genetic Programming for High-Dimensional Symbolic Regression. IEEE Transactions on Evolutionary Computation, 21(5):792-806, 2017. details

  45. Harith Al-Sahaf and Ausama Al-Sahaf and Bing Xue and Mark Johnston and Mengjie Zhang. Automatically Evolving Rotation-Invariant Texture Image Descriptors by Genetic Programming. IEEE Transactions on Evolutionary Computation, 21(1):83-101, 2017. details

  46. Binh Tran and Bing Xue and Mengjie Zhang. Genetic programming for feature construction and selection in classification on high-dimensional data. Memetic Computing, 8(1):3-15, 2016. details

  47. Bing Xue and Mengjie Zhang and Will N. Browne and Xin Yao. A Survey on Evolutionary Computation Approaches to Feature Selection. IEEE Transactions on Evolutionary Computation, 20(4):606-626, 2016. details

  48. Ying Bi and Bing Xue and Pablo Mesejo and Stefano Cagnoni and Mengjie Zhang. A survey on evolutionary computation for computer vision and image analysis: Past, present, and future trends. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  49. Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  50. Ying Bi and Bing Xue and Mengjie Zhang. Instance Selection-Based Surrogate-Assisted Genetic Programming for Feature Learning in Image Classification. IEEE Transactions on Cybernetics. details

  51. Ying Bi and Bing Xue and Mengjie Zhang. Multitask Feature Learning as Multiobjective Optimization: A New Genetic Programming Approach to Image Classification. IEEE Transactions on Cybernetics. Accepted for future publication. details

  52. Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming-Based Discriminative Feature Learning for Low-Quality Image Classification. IEEE Transactions on Cybernetics. details

  53. Qinglan Fan and Ying Bi and Bing Xue and Mengjie Zhang. A Global and Local Surrogate-Assisted Genetic Programming Approach to Image Classification. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  54. Qinglan Fan and Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming for Image Classification: A New Program Representation with Flexible Feature Reuse. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  55. 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. Accepted for future publication. details

  56. Ying Bi and Bing Xue and Dana Briscoe and Ross Vennell and Mengjie Zhang. A new artificial intelligent approach to buoy detection for mussel farming. Journal of the Royal Society of New Zealand. details

Genetic Programming Books by Bing Xue

Genetic Programming Conference proceedings edited by Bing Xue

Genetic Programming conference papers by Bing Xue

  1. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Multi-objective Genetic Programming with the Adaptive Weighted Splines Representation for Symbolic Regression. In Eric Medvet and Gisele Pappa and Bing Xue editors, EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, volume 13223, pages 51-67, Madrid, Spain, 2022. Springer Verlag. details

  2. Yunhan Yang and Bing Xue and Linley Jesson and Mengjie Zhang. Genetic Programming for Symbolic Regression: A Study on Fish Weight Prediction. In 2021 IEEE Congress on Evolutionary Computation (CEC), pages 588-595, 2021. details

  3. Zichu Yan and Ying Bi and Bing Xue and Mengjie Zhang. Automatically Extracting Features Using Genetic Programming for Low-Quality Fish Image Classification. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 2015-2022, Krakow, Poland, 2021. details

  4. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Multi-objective Genetic Programming for Symbolic Regression with the Adaptive Weighted Splines Representation. 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 165-166, internet, 2021. Association for Computing Machinery. details

  5. 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

  6. Qinglan Fan and Ying Bi and Bing Xue and Mengjie Zhang. Genetic Programming with A New Representation and A New Mutation Operator for Image 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 Companion, pages 249-250, internet, 2021. Association for Computing Machinery. details

  7. Hayden Andersen and Andrew Lensen and Bing Xue. Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 688-695, Krakow, Poland, 2021. details

  8. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. GP with a Hybrid Tree-vector Representation for Instance Selection and Symbolic Regression on Incomplete Data. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 604-611, Krakow, Poland, 2021. details

  9. Bing Xue and Mengjie Zhang. Evolutionary Computation for Feature Selection and Feature Construction. 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 1283-1312, internet, 2020. Association for Computing Machinery. Tutorial. details

  10. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Adaptive Weighted Splines: A New Representation to Genetic Programming for Symbolic Regression. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 1003-1011, internet, 2020. Association for Computing Machinery. details

  11. 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

  12. 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

  13. Abigail McGhie and Bing Xue and Mengjie Zhang. GPCNN: Evolving Convolutional Neural Networks using Genetic Programming. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pages 2684-2691, 2020. details

  14. Qinglan Fan and Bing Xue and Mengjie Zhang. A Region Adaptive Image Classification Approach Using Genetic Programming. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24346, internet, 2020. IEEE Press. details

  15. Benjamin P. Evans and Bing Xue and Mengjie Zhang. Improving Generalisation of AutoML Systems with Dynamic Fitness Evaluations. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 324-332, internet, 2020. Association for Computing Machinery. details

  16. Benjamin Evans and Bing Xue and Mengjie Zhang. An Adaptive and Near Parameter-free Evolutionary Computation Approach Towards True Automation in AutoML. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation (CEC), 2020. details

  17. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming-Based Selection of Imputation Methods in Symbolic Regression with Missing Values. In Marcus Gallagher and Nour Moustafa and Erandi Lakshika editors, AI 2020: Advances in Artificial Intelligence - 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29-30, 2020, Proceedings, volume 12576, pages 163-175, 2020. Springer. details

  18. Qi Chen and Bing Xue and Mengjie Zhang. Improving Symbolic Regression Based on Correlation between Residuals and Variables. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 922-930, internet, 2020. Association for Computing Machinery. details

  19. 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

  20. 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

  21. 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

  22. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Data Imputation for Symbolic Regression with Missing Values: A Comparative Study. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pages 2093-2100, 2020. details

  23. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multi-Tree Genetic Programming for Feature Construction-Based Domain Adaptation in Symbolic Regression with Incomplete Data. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 913-921, internet, 2020. Association for Computing Machinery. details

  24. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Hessian Complexity Measure for Genetic Programming-based Imputation Predictor Selection in Symbolic Regression with Incomplete Data. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming, volume 12101, pages 1-17, Seville, Spain, 2020. Springer Verlag. details

  25. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Multi-Tree Genetic Programming-based Transformation for Transfer Learning in Symbolic Regression with Highly Incomplete Data. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24250, internet, 2020. IEEE Press. details

  26. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming with Noise Sensitivity for Imputation Predictor Selection in Symbolic Regression with Incomplete Data. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24344, internet, 2020. IEEE Press. details

  27. Qurrat Ul Ain and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. A Genetic Programming Approach to Feature Construction for Ensemble Learning in Skin Cancer Detection. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 1186-1194, internet, 2020. Association for Computing Machinery. details

  28. Qurrat Ul Ain and Bing Xue and Harith Al-Sahaf and Mengjie Zhang. Multi-tree Genetic Programming with A New Fitness Function for Melanoma Detection. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 880-887, Wellington, New Zealand, 2019. IEEE Press. details

  29. Qurrat Ul Ain and Bing Xue and Harith Al-Sahaf and Mengjie Zhang. Genetic Programming for Multiple Feature Construction in Skin Cancer Image Classification. In 2019 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2019. details

  30. Christian Raymond and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming with Rademacher Complexity for Symbolic Regression. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 2657-2664, Wellington, New Zealand, 2019. IEEE Press. details

  31. 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

  32. 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

  33. 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

  34. Brandon Muller and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. Transfer learning: a building block selection mechanism in genetic programming for symbolic regression. 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 350-351, Prague, Czech Republic, 2019. ACM. details

  35. Andrew Lensen and Bing Xue and Mengjie Zhang. Can Genetic Programming Do Manifold Learning Too?. In Lukas Sekanina and Ting Hu and Nuno Lourenco editors, EuroGP 2019: Proceedings of the 22nd European Conference on Genetic Programming, volume 11451, pages 114-130, Leipzig, Germany, 2019. Springer Verlag. Best paper. details

  36. Wenlong Fu and Bing Xue and Xiaoying Gao and Mengjie Zhang. Genetic Programming based Transfer Learning for Document Classification with Self-taught and Ensemble Learning. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 2260-2267, Wellington, New Zealand, 2019. IEEE Press. details

  37. Benjamin P. Evans and Bing Xue and Mengjie Zhang. What's inside the black-box?: a genetic programming method for interpreting complex machine learning models. 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 1012-1020, Prague, Czech Republic, 2019. ACM. details

  38. Samaneh Azari and Bing Xue and Mengjie Zhang and Lifeng Peng. Improving the Results of De novo Peptide Identification via Tandem Mass Spectrometry Using a Genetic Programming-Based Scoring Function for Re-ranking Peptide-Spectrum Matches. In Abhaya C. Nayak and Alok Sharma editors, PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Cuvu, Yanuca Island, Fiji, August 26-30, 2019, Proceedings, Part III, volume 11672, pages 474-487, 2019. Springer. details

  39. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming for Imputation Predictor Selection and Ranking in Symbolic Regression with High-Dimensional Incomplete Data. In Jixue Liu and James Bailey editors, AI 2019: Advances in Artificial Intelligence - 32nd Australasian Joint Conference, Adelaide, SA, Australia, December 2-5, 2019, Proceedings, volume 11919, pages 523-535, 2019. Springer. details

  40. Samaneh Azari and Bing Xue and Mengjie Zhang and Lifeng Peng. A Decomposition Based Multi-objective Genetic Programming Algorithm for Classification of Highly Imbalanced Tandem Mass Spectrometry. In Shivakumara Palaiahnakote and Gabriella Sanniti di Baja and Liang Wang and Wei Qi Yan editors, Pattern Recognition - 5th Asian Conference, ACPR 2019, Auckland, New Zealand, November 26-29, 2019, Revised Selected Papers, Part II, volume 12047, pages 449-463, 2019. Springer. details

  41. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. Genetic Programming-Based Simultaneous Feature Selection and Imputation for Symbolic Regression with Incomplete Data. In Shivakumara Palaiahnakote and Gabriella Sanniti di Baja and Liang Wang and Wei Qi Yan editors, Pattern Recognition - 5th Asian Conference, ACPR 2019, Auckland, New Zealand, November 26-29, 2019, Revised Selected Papers, Part II, volume 12047, pages 566-579, 2019. Springer. details

  42. Qi Chen and Bing Xue and Mengjie Zhang. Differential evolution for instance based transfer learning in genetic programming for symbolic regression. 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 161-162, Prague, Czech Republic, 2019. ACM. details

  43. Qi Chen and Bing Xue and Mengjie Zhang. Instance based Transfer Learning for Genetic Programming for Symbolic Regression. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 3006-3013, Wellington, New Zealand, 2019. IEEE Press. details

  44. 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

  45. 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

  46. Samaneh Azari and Bing Xue and Mengjie Zhang and Lifeng Peng. Learning to Rank Peptide-Spectrum Matches Using Genetic Programming. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 3244-3251, Wellington, New Zealand, 2019. IEEE Press. details

  47. Baligh Al-Helali and Qi Chen and Bing Xue and Mengjie Zhang. A Genetic Programming-based Wrapper Imputation Method for Symbolic Regression with Incomplete Data. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pages 2395-2402, 2019. details

  48. Shima Afzali and Harith Al-Sahaf and Bing Xue and Christopher Hollitt and Mengjie Zhang. Genetic Programming for Feature Selection and Feature Combination in Salient Object Detection. In Paul Kaufmann and Pedro A. Castillo editors, 22nd International Conference, EvoApplications 2019, volume 11454, pages 308-324, Leipzig, Germany, 2019. Springer Verlag. details

  49. 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

  50. 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

  51. Shima Afzali and Harith Al-Sahaf and Bing Xue and Christopher Hollitt and Mengjie Zhang. A Genetic Programming Approach for Constructing Foreground and Background Saliency Features for Salient Object Detection. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, Wellington, New Zealand, 2018. Springer. details

  52. Cao Truong Tran and Mengjie Zhang and Bing Xue and Peter Andreae. Genetic Programming with Interval Functions and Ensemble Learning for Classification with Incomplete Data. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, pages 577-589, Wellington, New Zealand, 2018. Springer. details

  53. 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

  54. Yi Liu2 and Will N. Browne and Bing Xue. Adapting Bagging and Boosting to Learning Classifier Systems. In Stefano Cagnoni and Mengjie Zhang editors, 21st International Conference on the Applications of Evolutionary Computation, EvoIASP 2018, volume 10784, pages 405-420, Parma, Italy, 2018. Springer. details

  55. Andrew Lensen and Bing Xue and Mengjie Zhang. Automatically evolving difficult benchmark feature selection datasets with genetic programming. In Hernan Aguirre and Keiki Takadama and Hisashi Handa and Arnaud Liefooghe and Tomohiro Yoshikawa and Andrew M. Sutton and Satoshi Ono and Francisco Chicano and Shinichi Shirakawa and Zdenek Vasicek and Roderich Gross and Andries Engelbrecht and Emma Hart and Sebastian Risi and Ekart Aniko and Julian Togelius and Sebastien Verel and Christian Blum and Will Browne and Yusuke Nojima and Tea Tusar and Qingfu Zhang and Nikolaus Hansen and Jose Antonio Lozano and Dirk Thierens and Tian-Li Yu and Juergen Branke and Yaochu Jin and Sara Silva and Hitoshi Iba and Anna I Esparcia-Alcazar and Thomas Bartz-Beielstein and Federica Sarro and Giuliano Antoniol and Anne Auger and Per Kristian Lehre editors, GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference, pages 458-465, Kyoto, Japan, 2018. ACM. details

  56. Andrew Lensen and Bing Xue and Mengjie Zhang. Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming. In Mauro Castelli and Lukas Sekanina and Mengjie Zhang and Stefano Cagnoni and Pablo Garcia-Sanchez editors, EuroGP 2018: Proceedings of the 21st European Conference on Genetic Programming, volume 10781, pages 84-100, Parma, Italy, 2018. Springer Verlag. details

  57. Benjamin Evans and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. Evolutionary Deep Learning: A Genetic Programming Approach to Image Classification. In Marley Vellasco editor, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, 2018. IEEE. details

  58. 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

  59. 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

  60. Samaneh Azari and Mengjie Zhang and Bing Xue and Lifeng Peng. Genetic Programming for Preprocessing Tandem Mass Spectra to Improve the Reliability of Peptide Identification. In Marley Vellasco editor, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, 2018. IEEE. details

  61. Qurrat Ul Ain and Bing Xue and Harith Al-Sahaf and Mengjie Zhang. Genetic Programming for Feature Selection and Feature Construction in Skin Cancer Image Classification. In Xin Geng and Byeong-Ho Kang editors, PRICAI 2018: Trends in Artificial Intelligence - 15th Pacific Rim International Conference on Artificial Intelligence, Proceedings, Part I, volume 11012, pages 732-745, Nanjing, China, 2018. Springer. details

  62. Qurrat Ul Ain and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. A Multi-tree Genetic Programming Representation for Melanoma Detection Using Local and Global Features. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, pages 111-123, Wellington, New Zealand, 2018. Springer. details

  63. Tessa Phillips and Mengjie Zhang and Bing Xue. Genetic programming for solving common and domain-independent generic recursive problems. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 1279-1286, Donostia, San Sebastian, Spain, 2017. IEEE. details

  64. Damien O'Neill and Harith Al-Sahaf and Bing Xue and Mengjie Zhang. Common subtrees in related problems: A novel transfer learning approach for genetic programming. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 1287-1294, Donostia, San Sebastian, Spain, 2017. IEEE. details

  65. Andrew Lensen and Bing Xue and Mengjie Zhang. New Representations in Genetic Programming for Feature Construction in k-Means Clustering. In Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin editors, Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL-2017, volume 10593, pages 543-555, Shenzhen, China, 2017. Springer. details

  66. Wenlong Fu and Bing Xue and Mengjie Zhang and Xiaoying Gao. Transductive Transfer Learning in Genetic Programming for Document Classification. In Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin editors, Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, volume 10593, pages 556-568, Shenzhen, China, 2017. Springer. details

  67. Harith Al-Sahaf and Bing Xue and Mengjie Zhang. A Multitree Genetic Programming Representation for Automatically Evolving Texture Image Descriptors. In Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin editors, Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, volume 10593, pages 499-511, Shenzhen, China, 2017. Springer. details

  68. Qi Chen and Mengjie Zhang and Bing Xue. Geometric Semantic Genetic Programming with Perpendicular Crossover and Random Segment Mutation for Symbolic Regression. In Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin editors, Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, volume 10593, pages 422-434, Shenzhen, China, 2017. Springer. details

  69. Binh Tran and Bing Xue and Mengjie Zhang. Class Dependent Multiple Feature Construction Using Genetic Programming for High-Dimensional Data. 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 182-194, 2017. Springer. details

  70. 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

  71. Qi Chen and Mengjie Zhang and Bing Xue. Genetic Programming with Embedded Feature Construction for High-Dimensional Symbolic Regression. In Intelligent and Evolutionary Systems, 2017. Springer. details

  72. Qurrat Ul Ain and Bing Xue and Harith Al-Sahaf and Mengjie Zhang. Genetic programming for skin cancer detection in dermoscopic images. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 2420-2427, Donostia, San Sebastian, Spain, 2017. IEEE. details

  73. Cao Truong Tran and Mengjie Zhang and Peter Andreae and Bing Xue. Genetic Programming Based Feature Construction for Classification with Incomplete Data. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 1033-1040, Berlin, Germany, 2017. ACM. details

  74. Cao Truong Tran and Mengjie Zhang and Peter Andreae and Bing Xue. Multiple Imputation and Genetic Programming for Classification with Incomplete Data. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 521-528, Berlin, Germany, 2017. ACM. details

  75. Binh Tran and Bing Xue and Mengjie Zhang. Using Feature Clustering for GP-Based Feature Construction on High-Dimensional Data. In Mauro Castelli and James McDermott and Lukas Sekanina editors, EuroGP 2017: Proceedings of the 20th European Conference on Genetic Programming, volume 10196, pages 210-226, Amsterdam, 2017. Springer Verlag. details

  76. Andrew Lensen and Bing Xue and Mengjie Zhang. Improving K-means Clustering with Genetic Programming for Feature Construction. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 237-238, Berlin, Germany, 2017. ACM. details

  77. Andrew Lensen and Bing Xue and Mengjie Zhang. GPGC: Genetic Programming for Automatic Clustering Using a Flexible Non-hyper-spherical Graph-based Approach. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 449-456, Berlin, Germany, 2017. ACM. details

  78. Qi Chen and Mengjie Zhang and Bing Xue. New Geometric Semantic Operators in Genetic Programming: Perpendicular Crossover and Random Segment Mutation. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 223-224, Berlin, Germany, 2017. ACM. details

  79. Qi Chen and Bing Xue and Yi Mei and Mengjie Zhang. Geometric Semantic Crossover with an Angle-aware Mating Scheme in Genetic Programming for Symbolic Regression. In Mauro Castelli and James McDermott and Lukas Sekanina editors, EuroGP 2017: Proceedings of the 20th European Conference on Genetic Programming, volume 10196, pages 229-245, Amsterdam, 2017. Springer Verlag. details

  80. 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

  81. Harith Al-Sahaf and Bing Xue and Mengjie Zhang. Evolving Texture Image Descriptors Using a Multitree Genetic Programming Representation. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 219-220, Berlin, Germany, 2017. ACM. details

  82. Muhammad Iqbal and Bing Xue and Mengjie Zhang. Reusing Extracted Knowledge in Genetic Programming to Solve Complex Texture Image Classification Problems. In James Bailey and Latifur Khan and Takashi Washio and Gillian Dobbie and Joshua Zhexue Huang and Ruili Wang editors, Advances in Knowledge Discovery and Data Mining - 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part II, volume 9652, pages 117-129, 2016. Springer. details

  83. Soha Ahmed and Mengjie Zhang and Lifeng Peng and Bing Xue. A Multi-objective Genetic Programming Biomarker Detection Approach in Mass Spectrometry Data. In Giovanni Squillero and Paolo Burelli editors, 19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016, volume 9597, pages 106-122, Porto, Portugal, 2016. Springer. details

  84. Mengjie Zhang and Bing Xue. Evolutionary Computation for Feature Selection and Feature Construction. In Tobias Friedrich and Frank Neumann and Andrew M. Sutton and Martin Middendorf and Xiaodong Li and Emma Hart and Mengjie Zhang and Youhei Akimoto and Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and Daniele Loiacono and Julian Togelius and Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and Faustino Gomez and Carlos M. Fonseca and Heike Trautmann and Alberto Moraglio and William F. Punch and Krzysztof Krawiec and Zdenek Vasicek and Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and Boris Naujoks and Enrique Alba and Gabriela Ochoa and Simon Poulding and Dirk Sudholt and Timo Koetzing editors, GECCO '16 Companion: Proceedings of the Companion Publication of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 861-881, Denver, Colorado, USA, 2016. ACM. tutorial. details

  85. Binh Tran and Mengjie Zhang and Bing Xue. Multiple feature construction in classification on high-dimensional data using GP. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 2016. details

  86. Cao Truong Tran and Mengjie Zhang and Peter Andreae and Bing Xue. Directly Constructing Multiple Features for Classification with Missing Data using Genetic Programming with Interval Functions. In Tobias Friedrich and Frank Neumann and Andrew M. Sutton and Martin Middendorf and Xiaodong Li and Emma Hart and Mengjie Zhang and Youhei Akimoto and Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and Daniele Loiacono and Julian Togelius and Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and Faustino Gomez and Carlos M. Fonseca and Heike Trautmann and Alberto Moraglio and William F. Punch and Krzysztof Krawiec and Zdenek Vasicek and Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and Boris Naujoks and Enrique Alba and Gabriela Ochoa and Simon Poulding and Dirk Sudholt and Timo Koetzing editors, GECCO '16 Companion: Proceedings of the Companion Publication of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 69-70, Denver, USA, 2016. ACM. details

  87. Tessa Phillips and Mengjie Zhang and Bing Xue. Genetic Programming for Evolving Programs with Recursive Structures. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 5044-5051, Vancouver, 2016. IEEE Press. details

  88. Andrew Lensen and Harith Al-Sahaf and Mengjie Zhang and Bing Xue. Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data. In Malcolm I. Heywood and James McDermott and Mauro Castelli and Ernesto Costa and Kevin Sim editors, EuroGP 2016: Proceedings of the 19th European Conference on Genetic Programming, volume 9594, pages 51-67, Porto, Portugal, 2016. Springer Verlag. details

  89. Muhammad Iqbal and Mengjie Zhang and Bing Xue. Improving Classification on Images by Extracting and Transferring Knowledge in Genetic Programming. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 3582-3589, Vancouver, 2016. IEEE Press. details

  90. Edward Haslam and Bing Xue and Mengjie Zhang. Further Investigation on Genetic Programming with Transfer Learning for Symbolic Regression. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 3598-3605, Vancouver, 2016. IEEE Press. details

  91. Qi Chen and Mengjie Zhang and Bing Cue. Improving Generalisation of Genetic Programming for Symbolic Regression with Structural Risk Minimisation. In Tobias Friedrich editor, GECCO '16: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 709-716, Denver, USA, 2016. ACM. details

  92. Qi Chen and Bing Xue and Ben Niu and Mengjie Zhang. Improving Generalisation of Genetic Programming for High-Dimensional Symbolic Regression with Feature Selection. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 3793-3800, Vancouver, 2016. IEEE Press. details

  93. Andrew Lensen and Harith Al-Sahaf and Mengjie Zhang and Bing Xue. A hybrid Genetic Programming approach to feature detection and image classification. In 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015. details

  94. Qi Chen and Bing Xue and Mengjie Zhang. Generalisation and Domain Adaptation in GP with Gradient Descent for Symbolic Regression. In Yadahiko Murata editor, Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015), pages 1137-1144, Sendai, Japan, 2015. IEEE Press. details

  95. Soha Ahmed and Mengjie Zhang and Lifeng Peng and Bing Xue. Genetic Programming for Measuring Peptide Detectability. In Grant Dick and Will N. Browne and Peter A. Whigham and Mengjie Zhang and Lam Thu Bui and Hisao Ishibuchi and Yaochu Jin and Xiaodong Li and Yuhui Shi and Pramod Singh and Kay Chen Tan and Ke Tang editors, Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings, volume 8886, pages 593-604, 2014. Springer. details

  96. Soha Ahmed and Mengjie Zhang and Lifeng Peng and Bing Xue. Multiple feature construction for effective biomarker identification and classification using genetic programming. In Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. Montes de Oca and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges editors, GECCO '14: Proceedings of the 2014 conference on Genetic and evolutionary computation, pages 249-256, Vancouver, BC, Canada, 2014. ACM. details

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