6,927 research outputs found
Templates for Convex Cone Problems with Applications to Sparse Signal Recovery
This paper develops a general framework for solving a variety of convex cone
problems that frequently arise in signal processing, machine learning,
statistics, and other fields. The approach works as follows: first, determine a
conic formulation of the problem; second, determine its dual; third, apply
smoothing; and fourth, solve using an optimal first-order method. A merit of
this approach is its flexibility: for example, all compressed sensing problems
can be solved via this approach. These include models with objective
functionals such as the total-variation norm, ||Wx||_1 where W is arbitrary, or
a combination thereof. In addition, the paper also introduces a number of
technical contributions such as a novel continuation scheme, a novel approach
for controlling the step size, and some new results showing that the smooth and
unsmoothed problems are sometimes formally equivalent. Combined with our
framework, these lead to novel, stable and computationally efficient
algorithms. For instance, our general implementation is competitive with
state-of-the-art methods for solving intensively studied problems such as the
LASSO. Further, numerical experiments show that one can solve the Dantzig
selector problem, for which no efficient large-scale solvers exist, in a few
hundred iterations. Finally, the paper is accompanied with a software release.
This software is not a single, monolithic solver; rather, it is a suite of
programs and routines designed to serve as building blocks for constructing
complete algorithms.Comment: The TFOCS software is available at http://tfocs.stanford.edu This
version has updated reference
LHC Missing-Transverse-Energy Constraints on Models with Universal Extra Dimensions
We consider the performance of the ATLAS and CMS searches for events with
missing transverse energy, which were originally motivated by supersymmetry, in
constraining extensions of the Standard Model based on extra dimensions, in
which the mass differences between recurrences at the same level are
generically smaller than the mass hierarchies in typical supersymmetric models.
We consider first a toy model with pair-production of a single vector-like
quark U1 decaying into a spin-zero stable particle A1 and jet, exploring the
sensitivity of the CMS alphaT and ATLAS meff analysis to U1 mass and the U1-A1
mass difference. For this purpose we use versions of the Delphes generic
detector simulation with CMS and ATLAS cards, which have been shown to
reproduce the published results of CMS and ATLAS searches for supersymmetry. We
then explore the sensitivity of these searches to a specific model with two
universal extra dimensions, whose signal is dominated by the pair production of
quark recurrences, including searches with leptons. We find that the LHC
searches have greater sensitivity to this more realistic model, due partly to
the contributions of signatures with leptons, and partly to events with large
missing transverse energy generated by the decays of higher-level Kaluza-Klein
recurrences. We find that the CMS alphaT analysis with ~5/fb of data at 7 TeV
excludes a recurrence scale of 600 GeV at a confidence level above 99%,
increasing to 99.9% when combined with the CMS single-lepton search, whereas a
recurrence scale of 700 GeV is disfavoured at the 72% confidence level.Comment: 29 pages, 11 figures, 5 tables, references adde
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