—Using high-rate theory approximations we introduce flexible practical quantizers based on possibly non-Gaussian models in both the constrained resolution (CR) and the constrain...
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
A study of generalization error in signal detection by multiple spatially-distributed and -correlated sensors is provided when the detection rule is learned from a finite number ...
The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data...
Alin Florindor Murarasu, Josef Weidendorfer, Gerri...
We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k...