10,895 research outputs found
Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms
In this note we aim at putting more emphasis on the fact that trying to solve
non-convex optimization problems with coordinate-descent iterative linear
matrix inequality algorithms leads to suboptimal solutions, and put forward
other optimization methods better equipped to deal with such problems (having
theoretical convergence guarantees and/or being more efficient in practice).
This fact, already outlined at several places in the literature, still appears
to be disregarded by a sizable part of the systems and control community. Thus,
main elements on this issue and better optimization alternatives are presented
and illustrated by means of an example.Comment: 3 pages. Main experimental results reproducible from files available
on http://www.mathworks.com/matlabcentral/fileexchange/33219 This work has
been submitted to the IEEE for possible publication. Copyright may be
transferred without notice, after which this version may no longer be
accessibl
Divide and conquer in ABC: Expectation-Progagation algorithms for likelihood-free inference
ABC algorithms are notoriously expensive in computing time, as they require
simulating many complete artificial datasets from the model. We advocate in
this paper a "divide and conquer" approach to ABC, where we split the
likelihood into n factors, and combine in some way n "local" ABC approximations
of each factor. This has two advantages: (a) such an approach is typically much
faster than standard ABC and (b) it makes it possible to use local summary
statistics (i.e. summary statistics that depend only on the data-points that
correspond to a single factor), rather than global summary statistics (that
depend on the complete dataset). This greatly alleviates the bias introduced by
summary statistics, and even removes it entirely in situations where local
summary statistics are simply the identity function.
We focus on EP (Expectation-Propagation), a convenient and powerful way to
combine n local approximations into a global approximation. Compared to the EP-
ABC approach of Barthelm\'e and Chopin (2014), we present two variations, one
based on the parallel EP algorithm of Cseke and Heskes (2011), which has the
advantage of being implementable on a parallel architecture, and one version
which bridges the gap between standard EP and parallel EP. We illustrate our
approach with an expensive application of ABC, namely inference on spatial
extremes.Comment: To appear in the forthcoming Handbook of Approximate Bayesian
Computation (ABC), edited by S. Sisson, L. Fan, and M. Beaumon
Mode-coupling theory of the glass transition for confined fluids
We present a detailed derivation of a microscopic theory for the glass
transition of a liquid enclosed between two parallel walls relying on a
mode-coupling approximation. This geometry lacks translational invariance
perpendicular to the walls, which implies that the density profile and the
density-density correlation function depends explicitly on the distances to the
walls. We discuss the residual symmetry properties in slab geometry and
introduce a symmetry adapted complete set of two-point correlation functions.
Since the currents naturally split into components parallel and perpendicular
to the walls the mathematical structure of the theory differs from the
established mode-coupling equations in bulk. We prove that the equations for
the nonergodicity parameters still display a covariance property similar to
bulk liquids.Comment: 16 pages; to be published in PR
Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation
In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by the recognition that policymaking institutions need to process large quantities of information. Factor analysis is one popular way of doing this. Forecast combination is another, and it is on this that we concentrate. Bayesian model averaging methods have been widely advocated in this area, but a neglected frequentist approach is to use information theoretic based weights. We consider the use of model averaging in forecasting UK inflation with a large dataset from this perspective. We find that an information theoretic model averaging scheme can be a powerful alternative both to the more widely used Bayesian model averaging scheme and to factor models.Forecasting, Inflation, Bayesian model averaging, Akaike criteria, Forecast combining
On Determinants of Laplacians on Compact Riemann Surfaces Equipped with Pullbacks of Conical Metrics by Meromorphic Functions
Let be any conical (or smooth) metric of finite volume on the
Riemann sphere . On a compact Riemann surface of genus
consider a meromorphic funciton such that all poles and
critical points of are simple and no critical value of coincides with a
conical singularity of or . The pullback
of under has conical singularities of angles at the
critical points of and other conical singularities that are the preimages
of those of . We study the -regularized determinant
of the (Friedrichs extension of)
Laplace-Beltrami operator on as a functional on the moduli
space of pairs and obtain an explicit formula for .Comment: typos. arXiv admin note: text overlap with arXiv:1612.0866
Orbital Circularization of Hot and Cool Kepler Eclipsing Binaries
The rate of tidal circularization is predicted to be faster for relatively
cool stars with convective outer layers, compared to hotter stars with
radiative outer layers. Observing this effect is challenging, because it
requires large and well-characterized samples including both hot and cool
stars. Here we seek evidence for the predicted dependence of circularization
upon stellar type, using a sample of 945 eclipsing binaries observed by Kepler.
This sample complements earlier studies of this effect, which employed smaller
samples of better-characterized stars. For each Kepler binary we measure
based on the relative timing of the primary and secondary
eclipses. We examine the distribution of as a function of period
for binaries composed of hot stars, cool stars, and mixtures of the two types.
At the shortest periods, hot-hot binaries are most likely to be eccentric; for
periods shorter than 4 days, significant eccentricities occur frequently for
hot-hot binaries, but not for hot-cool or cool-cool binaries. This is in
qualitative agreement with theoretical expectations based on the slower
dissipation rates of hot stars. However, the interpretation of our results is
complicated by the largely unknown ages and evolutionary states of the stars in
our sample.Comment: Accepted for publication in Ap
Metatranscriptomes from diverse microbial communities: assessment of data reduction techniques for rigorous annotation
Background Metatranscriptome sequence data can contain highly redundant sequences from diverse populations of microbes and so data reduction techniques are often applied before taxonomic and functional annotation. For metagenomic data, it has been observed that the variable coverage and presence of closely related organisms can lead to fragmented assemblies containing chimeric contigs that may reduce the accuracy of downstream analyses and some advocate the use of alternate data reduction techniques. However, it is unclear how such data reduction techniques impact the annotation of metatranscriptome data and thus affect the interpretation of the results. Results To investigate the effect of such techniques on the annotation of metatranscriptome data we assess two commonly employed methods: clustering and de-novo assembly. To do this, we also developed an approach to simulate 454 and Illumina metatranscriptome data sets with varying degrees of taxonomic diversity. For the Illumina simulations, we found that a two-step approach of assembly followed by clustering of contigs and unassembled sequences produced the most accurate reflection of the real protein domain content of the sample. For the 454 simulations, the combined annotation of contigs and unassembled reads produced the most accurate protein domain annotations. Conclusions Based on these data we recommend that assembly be attempted, and that unassembled reads be included in the final annotation for metatranscriptome data, even from highly diverse environments as the resulting annotations should lead to a more accurate reflection of the transcriptional behaviour of the microbial population under investigation
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