Sharp analysis of low-rank kernel matrix approximations
F Bach - Conference on learning theory, 2013 - proceedings.mlr.press
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
Sharp analysis of low-rank kernel matrix approximations
F Bach - Conference on Learning Theory, 2013 - proceedings.mlr.press
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
[PDF][PDF] Sharp analysis of low-rank kernel matrix approximations
F Bach - jmlr.csail.mit.edu
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
[PDF][PDF] Sharp analysis of low-rank kernel matrix approximations
F Bach - translectures.videolectures.net
Sharp analysis of low-rank kernel matrix approximations Page 1 Sharp analysis of low-rank
kernel matrix approximations Francis Bach INRIA - Ecole Normale Supérieure, Paris, France …
kernel matrix approximations Francis Bach INRIA - Ecole Normale Supérieure, Paris, France …
Sharp analysis of low-rank kernel matrix approximations
F Bach - International Conference on Learning Theory (COLT), 2013 - hal.science
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
Sharp analysis of low-rank kernel matrix approximations
F Bach - 2012 - hal.univ-smb.fr
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
Sharp analysis of low-rank kernel matrix approximations
F Bach - arXiv preprint arXiv:1208.2015, 2012 - arxiv.org
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
Sharp analysis of low-rank kernel matrix approximations
F Bach - International Conference on Learning Theory (COLT), 2013 - inria.hal.science
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
Sharp analysis of low-rank kernel matrix approximations
F Bach - arXiv e-prints, 2012 - ui.adsabs.harvard.edu
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …
Sharp analysis of low-rank kernel matrix approximations
F Bach - HAL, 2013 - dml.mathdoc.fr
We consider supervised learning problems within the positive-definite kernel framework,
such as kernel ridge regression, kernel logistic regression or the support vector machine …
such as kernel ridge regression, kernel logistic regression or the support vector machine …