暂无分享,去创建一个
[1] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[2] Léon Bottou,et al. Local Learning Algorithms , 1992, Neural Computation.
[3] Steve R. Waterhouse,et al. Bayesian Methods for Mixtures of Experts , 1995, NIPS.
[4] Geoffrey E. Hinton,et al. Bayesian Learning for Neural Networks , 1995 .
[5] Christopher G. Atkeson,et al. Constructive Incremental Learning from Only Local Information , 1998, Neural Computation.
[6] Stefan Schaal,et al. Locally Weighted Projection Regression : An O(n) Algorithm for Incremental Real Time Learning in High Dimensional Space , 2000 .
[7] Carl E. Rasmussen,et al. Infinite Mixtures of Gaussian Process Experts , 2001, NIPS.
[8] George Eastman House,et al. Sparse Bayesian Learning and the Relevance Vector Machine , 2001 .
[9] Joaquin Quiñonero Candela,et al. Incremental Gaussian Processes , 2002, NIPS.
[10] Stefan Schaal,et al. The Bayesian Backtting Relevance Vector Machine , 2004 .
[11] Stefan Schaal,et al. The Bayesian backfitting relevance vector machine , 2004, ICML.
[12] Yuesheng Xu,et al. Universal Kernels , 2006, J. Mach. Learn. Res..
[13] Stefan Schaal,et al. Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model , 2007, IJCAI.
[14] Stefan Schaal,et al. Bayesian Kernel Shaping for Learning Control , 2008, NIPS.
[15] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[16] Michalis K. Titsias,et al. Variational Learning of Inducing Variables in Sparse Gaussian Processes , 2009, AISTATS.
[17] Warren B. Powell,et al. Dirichlet Process Mixtures of Generalized Linear Models , 2009, J. Mach. Learn. Res..