The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
—Oja’s principal subspace algorithm is a well-known and powerful technique for learning and tracking principal information in time series. A thorough investigation of the conve...
This paper finds and analyzes a formula for the total variation distance between iterations of riffle shuffles and iterations of "cut and then riffle shuffle". This allo...
We study convergence properties of empirical minimization of a stochastic strongly convex objective, where the stochastic component is linear. We show that the value attained by t...
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...