We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
This article proposes a new algorithm to compute the projection on the set of images whose total variation is bounded by a constant. The projection is computed through a dual form...
Distributed active sensing is a new sensing paradigm, where active sensors and passive sensors are distributed in a field, and collaboratively detect and track the objects. "E...
Given an oblique reflection map and functions , Dlim (the space of functions that have left and right limits at every point), the directional derivative () of along , evaluate...
We consider distributed linearly constrained minimum variance (LCMV) beamforming in a wireless sensor network. Each node computes an LCMV beamformer with node-specific constraint...