Learning Tensors From Partial Binary Measurements
We generalize the 1-bit matrix completion problem to higher order tensors. Consider a rank-
TSP Featured Articles
Learning of Tree-Structured Gaussian Graphical Models on Distributed Data Under Communication Constraints
In this paper, learning of tree-structured Gaussian graphical models from distributed data is addressed. In our model, samples are stored in a set of…
Read moreLorentzian-Model-Based Bayesian Analysis for Automated Estimation of Attenuated Resonance Spectrum
Extracting information from a signal exhibiting damped resonances is a challenging task in many practical cases due to the presence of noise and high…
Read moreRecovery of Independent Sparse Sources From Linear Mixtures Using Sparse Bayesian Learning
Classical algorithms for the multiple measurement vector (MMV) problem assume either independent columns for the solution matrix or certain models of…
Read moreDetection Theory for Union of Subspaces
The focus of this paper is on detection theory for union of subspaces (UoS). To this end, generalized likelihood ratio tests (GLRTs) are presented…
Read moreExploiting Sparsity in Tight-Dimensional Spaces for Piecewise Continuous Signal Recovery
Recovery of certain piecewise continuous signals from noisy observations has been a major challenge in sciences and engineering. In this paper, in a…
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