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In this paper we purpose a blockwise descent algorithm for grouppenalized multiresponse regression. Using a quasi-newton framework we extend this to group-penalized multinomial regression. We give a p...
For linear systems that contain unspecified parameters that lie in given intervals, we present a branch and bound algorithm for computing the maximum H_infinity-norm over the set of uncertain paramete...
We consider linear systems with unspecified parameters that lie between given upper and lower bounds. Except for a few special cases, the computation of many quantities of interest for such systems ca...
We describe an interior point algorithm for computing the upper bound for the structured singular value described in the paper by Fan, Tits and Doyle, IEEE Trans AC, Jan. 1991. We demonstrate the perf...
We consider nonlinear systems dx/dt=f(x(t)) where Df(x(t)) is known to lie in the convex hull of L n times n matrices A_1,ldots,A_L. For such systems, quadratic Lyapunov functions can be determined us...
We present a new algorithm for the global solution of optimization problems involving bilinear matrix inequalities (BMIs). The method is based on a technique known in large-scale and global optimizati...
The increasing application space of interconnection networks now encompasses several applications, such as packet routing and I/O interconnect, where the throughput of a routing algorithm, not just it...
We present an alternating augmented Lagrangian method for convex optimization problems where the cost function is the sum of two terms, one that is separable in the variable blocks, and a second that ...
Generalized additive models are an effective regression tool, popular in the statistics literature, that provide an automatic extension of traditional linear models to nonlinear systems. We pres...
This paper analyzes the convergence properties of an iterative Monte Carlo procedure proposed in the Physics literature for estimating the quasi-stationary distribution on a transient set of a Markov ...
If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential in...
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints.Here w...
We address the persistence and stability of three-dimensional vortex configurations in the discrete nonlinear Schrödinger equation and develop a symbolic package based on Wolfram’s MATHEMATICA fo...
We consider the computation of the permanent of a binary n by n matrix. It is well- known that the exact computation is a #P complete problem. A variety of Markov chain Monte Carlo (MCMC) computationa...
We establish optimal convergence rates for a decomposition-based scalable approach to kernel ridge regression. The method is simple to describe: it randomly partitions a dataset of size N into m subse...

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