The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
Abstract— This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a pre...
Practical sparse approximation algorithms (particularly greedy algorithms) suffer two significant drawbacks: they are difficult to implement in hardware, and they are inefficie...
Christopher J. Rozell, Don H. Johnson, Richard G. ...