The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack o...
Daniel Glasner, Tao Hu, Juan Nunez-Iglesias, Lou S...
This paper addresses source separation from a linear mixture under two assumptions: source sparsity and orthogonality of the mixing matrix. We propose efficient sparse separation...
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...