暂无分享,去创建一个
Guangming Shi | Yu Song | Fei Qi | Hang Yang | Zhaohui Xia | Chunhuan Lin | Gaoyang Tang | Guangrui Qian | Xiong An
[1] Sergio Escalera,et al. A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention , 2016, AutoML@ICML.
[2] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[3] Gisele L. Pappa,et al. RECIPE: A Grammar-Based Framework for Automatically Evolving Classification Pipelines , 2017, EuroGP.
[4] Randal S. Olson,et al. Automating Biomedical Data Science Through Tree-Based Pipeline Optimization , 2016, EvoApplications.
[5] Kevin Leyton-Brown,et al. Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms , 2012, KDD.
[6] Scott M. Williams,et al. A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction , 2007, Genetic epidemiology.
[7] Aaron Klein,et al. Efficient and Robust Automated Machine Learning , 2015, NIPS.
[8] Kevin Leyton-Brown,et al. Sequential Model-Based Optimization for General Algorithm Configuration , 2011, LION.
[9] Krzysztof Krawiec,et al. Semantic Backpropagation for Designing Search Operators in Genetic Programming , 2015, IEEE Transactions on Evolutionary Computation.
[10] Randal S. Olson,et al. PMLB: a large benchmark suite for machine learning evaluation and comparison , 2017, BioData Mining.
[11] Yoshua Bengio,et al. Random Search for Hyper-Parameter Optimization , 2012, J. Mach. Learn. Res..
[12] Quoc V. Le,et al. Large-Scale Evolution of Image Classifiers , 2017, ICML.
[13] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[14] Randal S. Olson,et al. Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science , 2016, GECCO.
[15] Julian Francis Miller,et al. Cartesian genetic programming , 2010, GECCO.
[16] Hugo Jair Escalante,et al. EvoDAG: A semantic Genetic Programming Python library , 2016, 2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC).
[17] Nando de Freitas,et al. A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning , 2010, ArXiv.
[18] Conor Ryan,et al. Handbook of Genetic Programming Applications , 2015, Springer International Publishing.
[19] John R. Koza,et al. Genetic programming 2 - automatic discovery of reusable programs , 1994, Complex Adaptive Systems.
[20] Ian H. Witten,et al. The WEKA data mining software: an update , 2009, SKDD.
[21] Luís Torgo,et al. OpenML: networked science in machine learning , 2014, SKDD.
[22] Hod Lipson,et al. Autostacker: a compositional evolutionary learning system , 2018, GECCO.
[23] A. Asuncion,et al. UCI Machine Learning Repository, University of California, Irvine, School of Information and Computer Sciences , 2007 .
[24] Hugo Jair Escalante,et al. Semantic Genetic Programming for Sentiment Analysis , 2015, NEO.
[25] Daniel A. Ashlock,et al. Evolving fractal art with a directed acyclic graph genetic programming representation , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).
[26] Kalyanmoy Deb,et al. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.
[27] Tobias Glasmachers,et al. Limits of End-to-End Learning , 2017, ACML.
[28] Nichael Lynn Cramer,et al. A Representation for the Adaptive Generation of Simple Sequential Programs , 1985, ICGA.
[29] A. B. Kahn,et al. Topological sorting of large networks , 1962, CACM.
[30] Udayan Khurana,et al. Automating Feature Engineering , 2016 .
[31] Christian Igel,et al. Evolutionary tuning of multiple SVM parameters , 2005, ESANN.
[32] Li Fei-Fei,et al. Progressive Neural Architecture Search , 2017, ECCV.
[33] Artus Krohn-Grimberghe,et al. AutoCompete: A Framework for Machine Learning Competition , 2015, ArXiv.
[34] Lars Kotthoff,et al. Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA , 2017, J. Mach. Learn. Res..
[35] Sergio Escalera,et al. Design of the 2015 ChaLearn AutoML challenge , 2015, IJCNN.
[36] Deepak S. Turaga,et al. Feature Engineering for Predictive Modeling using Reinforcement Learning , 2017, AAAI.
[37] Pavel Kordík,et al. Discovering predictive ensembles for transfer learning and meta-learning , 2017, Machine Learning.
[38] A. A. Ghorbani,et al. Stacked generalization in neural networks: generalization on statistically neutral problems , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).