Many statistical M-estimators are based on convex optimization problems formed by the weighted sum of a loss function with a norm-based regularizer. We analyze the convergence rat...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
We present an extension of the development of an alternating minimization (AM) method1 for the computation of a specimen's complex transmittance function (magnitude and phase...
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
Consider the space of two dimensional vector functions whose components and curl are square integrable with respect to the degenerate weight given by the radial variable. This spac...
Dylan M. Copeland, Jayadeep Gopalakrishnan, Minah ...
Abstract--An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefo...