Sparse Approximation of a Kernel Mean
نویسندگان
چکیده
منابع مشابه
A kernel-based RLS algorithm for nonlinear adaptive filtering using sparse approximation theory
In the last ten years, there has been an explosion of activity in the field of learning algorithms utilizing reproducing kernels, most notably for classification and regression. A common characteristic in kernelbased methods is that they deal with models whose order equals the number of input data, making them unsuitable for online applications. In this paper, we investigate a new kernel-based ...
متن کاملKernel Mean Shrinkage Estimators
A mean function in a reproducing kernel Hilbert space (RKHS), or a kernel mean, is central to kernel methods in that it is used by many classical algorithms such as kernel principal component analysis, and it also forms the core inference step of modern kernel methods that rely on embedding probability distributions in RKHSs. Given a finite sample, an empirical average has been used commonly as...
متن کاملSparse Kernel Regressors
Sparse kernel regressors have become popular by applying the support vector method to regression problems. Although this approach has been shown to exhibit excellent generalization properties in many experiments, it suffers from several drawbacks: the absence of probabilistic outputs, the restriction to Mercer kernels, and the steep growth of the number of support vectors with increasing size o...
متن کاملSparse Kernel Feature Analysis
Kernel Principal Component Analysis (KPCA) has proven to be a versatile tool for unsupervised learning, however at a high computational cost due to the dense expansions in terms of kernel functions. We overcome this problem by proposing a new class of feature extractors employing`1 norms in coeecient space instead of the reproducing kernel Hilbert space in which KPCA was originally formulated i...
متن کاملA Sparse Regular Approximation Lemma
We introduce a new variant of Szemerédi’s regularity lemma which we call the sparse regular approximation lemma (SRAL). The input to this lemma is a graph G of edge density p and parameters , δ, where we think of δ as a constant. The goal is to construct an -regular partition of G while having the freedom to add/remove up to δ|E(G)| edges. As we show here, this weaker variant of the regularity ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2017
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2016.2628353