Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Sparse representation in compressive sensing is gaining increasing attention due to its success in various applications. As we demonstrate in this paper, however, image sparse rep...
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of u...
The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwr...