In this paper we present several algorithms for performing all-to-many personalized communication on distributed memory parallel machines. We assume that each processor sends a di erent message (of potentially di erent size) to a subset of all the processors involved in the collective communication. The algorithms are based on decomposing the communication matrix into a set of partial permutati...

Tutte associates a V by V skew-symmetric matrix T , having indeterminate entries, with a graph G=(V,E). This matrix, called the Tutte matrix, has rank exactly twice the size of a maximum cardinality matching of G. Thus, to find the size of a maximum matching it suffices to compute the rank of T . We consider the more general problem of computing the rank of T +K where K is a real V by V skew-sy...

A quantum compiler is a software program for decomposing (“compiling”) an arbitrary unitary matrix into a sequence of elementary operations (SEO). The author of this paper is also the author of a quantum compiler called Qubiter. Qubiter uses a matrix decomposition called the Cosine-Sine Decomposition (CSD) that is well known in the field of Computational Linear Algebra. One way of measuring the...

We give an algorithm for the on-line learning of permutations. The algorithm maintains its uncertainty about the target permutation as a doubly stochastic weight matrix, and uses an efficient method for decomposing the weight matrix as a convex combination of permutations to make predictions. The weight matrix is updated by multiplying the current matrix entries by exponential factors, and an i...

Abstract Graphical models are a powerful tool to estimate high-dimensional inverse covariance (precision) matrix, which has been applied for portfolio allocation problem. The assumption made by these is sparsity of the precision matrix. However, when stock returns driven common factors, such does not hold. We address this limitation and develop framework, Factor Lasso (FGL), integrates graphica...

We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fluoroscopic intensity is the superimposition of intensity components of all the structures passed ...

The modified discrete cosine transform (MDCT) and inverse MDCT (IMDCT) are two of the most computational intensive operations in MPEG audio coding standards. A new mixed-radix algorithm for efficient computing the MDCT/IMDCT is presented. The proposed mixed-radix MDCT algorithm is composed of two recursive algorithms. The first algorithm, called the radix-2 decimation in frequency (DIF) algorit...

We address in this paper the parallelization of a recursive algorithm for triangular matrix inversion (TMI) based on the ‘Divide and Conquer’ (D&C) paradigm. A series of different versions of an original sequential algorithm are first presented. A theoretical performance study permits to establish an accurate comparison between the designed algorithms. Afterwards, we develop an optimal parallel...

Robust tensor CP decomposition involves decomposing a tensor into low rank and sparse components. We propose a novel non-convex iterative algorithm with guaranteed recovery. It alternates between lowrank CP decomposition through gradient ascent (a variant of the tensor power method), and hard thresholding of the residual. We prove convergence to the globally optimal solution under natural incoh...