We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
We present a novel weighted approach for shrinkage functions learning in image denoising. The proposed approach optimizes the shape of the shrinkage functions and maximizes denois...
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
We propose an acceleration scheme for real-time many-body dynamic collision detection. We kinetize the sweep and prune method for many-body collision pruning, extending its applic...
We consider the problem of constructing an erasure code for storage over a network when the data sources are distributed. Specifically, we assume that there are n storage nodes wit...
Alexandros G. Dimakis, Vinod M. Prabhakaran, Kanna...