Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Abstract. We study the following problem in a sovereign informationsharing setting: How to ensure that the individual participants, driven solely by self-interest, will behave hone...
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...