Open kastnerkyle opened 10 years ago
Specifics of kernel approximation for neural networks http://ivan-titov.org/papers/ijcnn05.pdf http://www.lce.hut.fi/~eiparvia/publ/KDIR10_cready_ParviainenEtAl.pdf http://cseweb.ucsd.edu/~saul/papers/neco10_arccos.pdf http://www.lce.hut.fi/~eiparvia/publ/KDIR_Parviainen_slides.pdf http://mitp-cogdev.mit.edu/sites/default/files/journalpdfs/089976698300017412.pdf
http://machinelearning.wustl.edu/mlpapers/paper_files/Genton01.pdf
Very interesting talk about learning the projection from the kernel... maybe it can be reversed somehow... http://www.kernel-methods.net/tutorials/KMtalk.pdf
Mixture Density Kernels.... very, very interesting http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.34
KernelBoosting? http://machinelearning.wustl.edu/mlpapers/paper_files/icml2006_HertzBW06.pdf
Learning Kernel from data http://www-bcf.usc.edu/~feisha/pubs/learning_kernel04.pdf
Data Dependent Kernel Map http://www.igi.tugraz.at/lehre/MLA/WS05/mla_2006_17_01.pdf
Deep neural kernels http://arxiv.org/pdf/1112.3712v1.pdf
Nice comment at the end about kernel contruction http://www.iip.ist.i.kyoto-u.ac.jp/member/cuturi/Teaching/KU/2011/FIS/Lec7.pdf
Kernel Cookbook http://mlg.eng.cam.ac.uk/duvenaud/cookbook/index.html
Hinton Learning Covariance from DBM http://www.cs.toronto.edu/~hinton/absps/dbngp.pdf
Convolutional Kernel Networks http://arxiv.org/abs/1406.3332
http://www.eric-kim.net/eric-kim-net/posts/1/kernel_trick.html
http://nbviewer.ipython.org/github/mirjalil/pattern_recognition/blob/master/ComponentAnalysis.ipynb#kpca-results