Programming in an open environment remains challenging because it requires combining modularity, security, concurrency, distribution, and dynamicity. In this paper, we propose an ...
Michael Lienhardt, Alan Schmitt, Jean-Bernard Stef...
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Abstract--In this paper, we investigate various channel estimators that exploit channel sparsity in the time and/or Doppler domain for a multicarrier underwater acoustic system. We...
Christian R. Berger, Shengli Zhou, James C. Preisi...