FlexGP
暂无分享,去创建一个
Kalyan Veeramachaneni | Una-May O'Reilly | Ignacio Arnaldo | Owen Derby | Una-May O’Reilly | K. Veeramachaneni | Ignacio Arnaldo | Owen Derby
[1] Trevor Hastie,et al. Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.
[2] Terence Soule,et al. Behavioral Diversity and a Probabilistically Optimal GP Ensemble , 2004, Genetic Programming and Evolvable Machines.
[3] Kalyan Veeramachaneni,et al. Learning regression ensembles with genetic programming at scale , 2013, GECCO '13.
[4] Jiri Matas,et al. On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[5] Jimmy J. Lin,et al. Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.
[6] Thomas G. Dietterich. Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.
[7] Juan Julián Merelo Guervós,et al. EvAg: a scalable peer-to-peer evolutionary algorithm , 2010, Genetic Programming and Evolvable Machines.
[8] H. Iba. Bagging, Boosting, and bloating in Genetic Programming , 1999 .
[9] Ke Wang,et al. Parallel learning to rank for information retrieval , 2011, SIGIR.
[10] Leonardo Vanneschi,et al. An Empirical Study of Multipopulation Genetic Programming , 2003, Genetic Programming and Evolvable Machines.
[11] Thomas G. Dietterich. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization , 2000, Machine Learning.
[12] Hod Lipson,et al. Distilling Free-Form Natural Laws from Experimental Data , 2009, Science.
[13] Juan Julián Merelo Guervós,et al. A Peer-to-Peer Approach to Genetic Programming , 2011, EuroGP.
[14] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[15] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[16] Anders Krogh,et al. Neural Network Ensembles, Cross Validation, and Active Learning , 1994, NIPS.
[17] Maarten Keijzer,et al. Improving Symbolic Regression with Interval Arithmetic and Linear Scaling , 2003, EuroGP.
[18] Giandomenico Spezzano,et al. A Jxta Based Asynchronous Peer-to-Peer Implementation of Genetic Programming , 2006, J. Softw..
[19] Krzysztof Krawiec,et al. Multiple regression genetic programming , 2014, GECCO.
[20] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[21] Xavier Llorà,et al. Scaling eCGA model building via data-intensive computing , 2010, IEEE Congress on Evolutionary Computation.
[22] William B. Langdon,et al. Combining Decision Trees and Neural Networks for Drug Discovery , 2002, EuroGP.
[23] Pier Luca Lanzi,et al. XCS with stack-based genetic programming , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[24] Giandomenico Spezzano,et al. Mining Distributed Evolving Data Streams Using Fractal GP Ensembles , 2007, EuroGP.
[25] Kalyan Veeramachaneni,et al. Flex-GP: Genetic Programming on the Cloud , 2012, EvoApplications.
[26] Una-May O'Reilly,et al. A Library to Run Evolutionary Algorithms in the Cloud Using MapReduce , 2012, EvoApplications.
[27] Lars Niklasson,et al. Genetically Evolved Trees Representing Ensembles , 2006, ICAISC.
[28] Thierry Bertin-Mahieux,et al. The Million Song Dataset , 2011, ISMIR.
[29] John Langford,et al. Sparse Online Learning via Truncated Gradient , 2008, NIPS.
[30] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[31] Xavier Llorà,et al. Scaling Genetic Algorithms Using MapReduce , 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.
[32] Mark Johnston,et al. Evolving Diverse Ensembles Using Genetic Programming for Classification With Unbalanced Data , 2013, IEEE Transactions on Evolutionary Computation.
[33] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[34] Owen C. Derby. FlexGP: a Scalable System for Factored Learning in the Cloud , 2013 .
[35] Dylan Sherry. FlexGP 2.0 : multiple levels of parallelism in distributed machine learning via genetic programming , 2013 .
[36] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[37] E. Vladislavleva. Model-based problem solving through symbolic regression via pareto genetic programming , 2008 .
[38] Márk Jelasity,et al. T-Man: Gossip-based fast overlay topology construction , 2009, Comput. Networks.
[39] Leonardo Vanneschi,et al. Operator equalisation for bloat free genetic programming and a survey of bloat control methods , 2011, Genetic Programming and Evolvable Machines.
[40] Mark Kotanchek,et al. Trustable symbolic regression models: using ensembles, interval arithmetic and pareto fronts to develop robust and trust-aware models , 2008 .
[41] Kalyan Veeramachaneni,et al. Evolutionary optimization of flavors , 2010, GECCO '10.
[42] Anne-Marie Kermarrec,et al. Gossiping in distributed systems , 2007, OPSR.
[43] J. Ross Quinlan,et al. Bagging, Boosting, and C4.5 , 1996, AAAI/IAAI, Vol. 1.
[44] Yuhong Yang. Adaptive Regression by Mixing , 2001 .
[45] Andy J. Keane,et al. A Data Parallel Approach for Large-Scale Gaussian Process Modeling , 2002, SDM.