Gradient boosting for kernelized output spaces
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Pierre Geurts | Louis Wehenkel | Florence d'Alché-Buc | P. Geurts | L. Wehenkel | Florence d'Alché-Buc
[1] J. Friedman. Stochastic gradient boosting , 2002 .
[2] J. Freidman,et al. Multivariate adaptive regression splines , 1991 .
[3] Bernhard Schölkopf,et al. Kernel Dependency Estimation , 2002, NIPS.
[4] Pierre Geurts,et al. Extremely randomized trees , 2006, Machine Learning.
[5] Yoshihiro Yamanishi,et al. Supervised enzyme network inference from the integration of genomic data and chemical information , 2005, ISMB.
[6] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[7] Pierre Geurts,et al. Kernelizing the output of tree-based methods , 2006, ICML '06.
[8] Gunnar Rätsch,et al. Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces , 2002, Machine Learning.
[9] Ben Taskar,et al. Learning structured prediction models: a large margin approach , 2005, ICML.
[10] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[11] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[12] Jason Weston,et al. A general regression technique for learning transductions , 2005, ICML '05.
[13] Peter L. Bartlett,et al. Boosting Algorithms as Gradient Descent , 1999, NIPS.
[14] R. Memisevic. An introduction to structured discriminative learning , 2006 .