In this paper we address the problem of pool based active learning, and provide an algorithm, called UPAL, that works by minimizing the unbiased estimator of the risk of a hypothe...
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...
Han Lun Yap, Armin Eftekhari, Michael B. Wakin, Ch...
We generally study the density of eigenvalues in unitary ensembles of random matrices from the recurrence coefficients with regularly varying conditions for the orthogonal polynomi...
Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as 1-minimization find the sparse...
Random projection has been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. It represents a computati...
Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yas...