Improved approximation guarantees for weighted matching in the semi-streaming model

We study the maximum weight matching problem in the semi-streaming model, and improve on the currently best one-pass algorithm due to Zelke (Proc. of STACS2008, pages 669-680) by devising a deterministic approach whose performance guarantee is 4.91+epsilon. In addition, we study preemptive online algorithms, a sub-class of one-pass algorithms where we are only allowed to maintain a feasible matching in memory at any point in time. All known results prior to Zelke's belong to this sub-class. We provide a lower bound of 4.967 on the competitive ratio of any such deterministic algorithm, and hence show that future improvements will have to store in memory a set of edges which is not necessarily a feasible matching

Efficient Isomorphism Testing for a Class of Group Extensions

The group isomorphism problem asks whether two given groups are isomorphic or not. Whereas the case where both groups are abelian is well understood and can be solved efficiently, very little is known about the complexity of isomorphism testing for nonabelian groups. In this paper we study this problem for a class of groups corresponding to one of the simplest ways of constructing nonabelian groups from abelian groups: the groups that are extensions of an abelian group A by a cyclic group of order m. We present an efficient algorithm solving the group isomorphism problem for all the groups of this class such that the order of A is coprime with m. More precisely, our algorithm runs in time almost linear in the orders of the input groups and works in the general setting where the groups are given as black-boxes.Comment: 17 pages, accepted to the STACS 2009 conferenc

A Backward Particle Interpretation of Feynman-Kac Formulae

We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals "on-the-fly" as well as their limiting occupation measures with a given precision degree that does not depend on the final time horizon. We provide uniform convergence results w.r.t. the time horizon parameter as well as functional central limit theorems and exponential concentration estimates. We also illustrate these results in the context of computational physics and imaginary time Schroedinger type partial differential equations, with a special interest in the numerical approximation of the invariant measure associated to $h$-processes

Author manuscript, published in "ACM-GECCO Genetic and Evolutionary Computation Conference (2009)" Benchmarking the Nelder-Mead Downhill Simplex Algorithm With Many Local Restarts

We benchmark the Nelder-Mead downhill simplex method on the noisefree BBOB-2009 testbed. A multistart strategy is applied on two levels. On a local level, at least ten restarts are conducted with a small number of iterations and reshaped simplex. On the global level independent restarts are launched until 10 5 D function evaluations are exceeded, for dimension D ≥ 20 ten times less. For low search space dimensions the algorithm shows very good results on many functions. It solves 24, 18, 11 and 7 of 24 functions in 2, 5

Division Algorithms for Bernstein Polynomials

Three division algorithms are presented for univariate Bernstein polynomials: an algorithm for finding the quotient and remainder of two univariate polynomials, an algorithm for calculating the GCD of an arbitrary collection of univariate polynomials, and an algorithm for computing a µ-basis for the syzygy module of an arbitrary collection of univariate polynomials. Division algorithms for multivariate Bernstein polynomials and analogues in the multivariate Bernstein setting of Gröbner bases are also discussed. All these algorithms are based on a simple ring isomorphism that converts each of these problems from the Bernstein basis to an equivalent problem in the monomial basis. This isomorphism allows all the computations to be performed using only the original Bernstein coefficients; no conversion to monomial coefficients is required

DOI: 10.1007/978-1-84882-299-3 From Second to Higher Order Tensors in Diffusion-MRI

Diffusion MRI, which is sensitive to the Brownian motion of molecules, has become today an excellent medical tool for probing the tissue micro-structure of cerebral white matter in vivo and non-invasively. It makes it possible to reconstruct fiber pathways and segment major fiber bundles that reflect the structures in the brain which are not visible to other non-invasive imaging modalities. Since this is possible without operating on the subject, but by integrating partial information from Diffusion Weighted Images into a reconstructed ’complete ’ image of diffusion, Diffusion MRI opens a whole new domain of image processing. Here we shall explore the role that tensors play in the mathematical model. We shall primarily deal with Cartesian tensors and begin with 2nd order tensors, since these are at the core of Diffusion Tensor Imaging. We shall then explore higher and even ordered symmetric tensors, that can take into account more complex micro-geometries of biological tissues such as axonal crossings in the white matter.

Author manuscript, published in "Alberto Mendelzon International Workshop on Foundations of Data Management (AMW) (2011)" Challenges for View-Based Query Answering over Probabilistic XML

Abstract. This is the first and preliminary study on answering queries using views in a probabilistic XML setting. We formalize the problem and study it under the two possible semantics for XML query results: with node identifiers and in their absence. Accordingly, we consider rewrite plans that can exploit a single view, by means of compensation, and plans that can use multiple views, by means of intersection. Since in probabilistic settings queries return answers with probabilities, the problem of rewriting goes beyond the classical one of retrieving answers from views. For both semantics of XML queries, we show that, even if the XML answers can be retrieved, the computation of their probabilities might not be possible. We give restrictions that make probabilistic rewriting feasible in polynomial time, and present some initial hardness results for this problem.

Repetitive model refactoring strategy for the design space exploration of intensive signal processing applications

Repetitive model refactoring strategy for the design space exploration of intensive signal processing application

Accelerated Invariant . . .

In this paper, we present Aspic, an automatic polyhedral invariant generation tool for flowcharts programs. Aspic implements an improved Linear Relation Analysis on numeric counter automata. The “accelerated” method improves precision by computing locally a precise overapproximation of a loop without using the widening operator. c2fsm is a C preprocessor that generates automata in the format required by Aspic. The experimental results show the performance and precision of the tools

Circuit-Switched Gossiping in 3-Dimensional Torus Networks.

In this paper we describe an efficient gossiping algorithm for short messages into the 3-dimensional torus networks (wrap-around or toroidal meshes) that uses synchronous circuit-switched routing. The algorithm is based on a recursive decomposition of a torus. It requires an optimal number of rounds and a quasi-optimal number of intermediate switch settings to gossip in a 7^i × 7^i × 7^i torus network