1,109,391 research outputs found
Linear Convergence on Positively Homogeneous Functions of a Comparison Based Step-Size Adaptive Randomized Search: the (1+1) ES with Generalized One-fifth Success Rule
In the context of unconstraint numerical optimization, this paper
investigates the global linear convergence of a simple probabilistic
derivative-free optimization algorithm (DFO). The algorithm samples a candidate
solution from a standard multivariate normal distribution scaled by a step-size
and centered in the current solution. This solution is accepted if it has a
better objective function value than the current one. Crucial to the algorithm
is the adaptation of the step-size that is done in order to maintain a certain
probability of success. The algorithm, already proposed in the 60's, is a
generalization of the well-known Rechenberg's Evolution Strategy (ES)
with one-fifth success rule which was also proposed by Devroye under the name
compound random search or by Schumer and Steiglitz under the name step-size
adaptive random search. In addition to be derivative-free, the algorithm is
function-value-free: it exploits the objective function only through
comparisons. It belongs to the class of comparison-based step-size adaptive
randomized search (CB-SARS). For the convergence analysis, we follow the
methodology developed in a companion paper for investigating linear convergence
of CB-SARS: by exploiting invariance properties of the algorithm, we turn the
study of global linear convergence on scaling-invariant functions into the
study of the stability of an underlying normalized Markov chain (MC). We hence
prove global linear convergence by studying the stability (irreducibility,
recurrence, positivity, geometric ergodicity) of the normalized MC associated
to the -ES. More precisely, we prove that starting from any initial
solution and any step-size, linear convergence with probability one and in
expectation occurs. Our proof holds on unimodal functions that are the
composite of strictly increasing functions by positively homogeneous functions
with degree (assumed also to be continuously differentiable). This
function class includes composite of norm functions but also non-quasi convex
functions. Because of the composition by a strictly increasing function, it
includes non continuous functions. We find that a sufficient condition for
global linear convergence is the step-size increase on linear functions, a
condition typically satisfied for standard parameter choices. While introduced
more than 40 years ago, we provide here the first proof of global linear
convergence for the -ES with generalized one-fifth success rule and the
first proof of linear convergence for a CB-SARS on such a class of functions
that includes non-quasi convex and non-continuous functions. Our proof also
holds on functions where linear convergence of some CB-SARS was previously
proven, namely convex-quadratic functions (including the well-know sphere
function)
D6-Brane Model Building on Z(2)xZ(6): MSSM-like and Left-Right Symmetric Models
We perform a systematic search for globally defined MSSM-like and left-right
symmetric models on D6-branes on the T6/Z(2)xZ(6)xOR orientifold with discrete
torsion. Our search is exhaustive for models that are independent of the value
of the one free complex structure modulus. Preliminary investigations suggest
that there exists one prototype of visible sector for MSSM-like and another for
left-right symmetric models with differences arising from various hidden sector
completions to global models. For each prototype, we provide the full matter
spectrum, as well as the Yukawa and other three-point couplings needed to
render vector-like matter states massive. This provides us with tentative
explanations for the mass hierarchies within the quark and lepton sectors. We
also observe that the MSSM-like models correspond to explicit realisations of
the supersymmetric DFSZ axion model, and that the left-right symmetric models
allow for global completions with either completely decoupled hidden sectors or
with some messenger states charged under both visible and hidden gauge groups.Comment: 1+95 pages, 5 figures, 40 table
Optimal Estimation of Ion-Channel Kinetics from Macroscopic Currents
Markov modeling provides an effective approach for modeling ion channel kinetics. There are several search algorithms for global fitting of macroscopic or single-channel currents across different experimental conditions. Here we present a particle swarm optimization(PSO)-based approach which, when used in combination with golden section search (GSS), can fit macroscopic voltage responses with a high degree of accuracy (errors within 1%) and reasonable amount of calculation time (less than 10 hours for 20 free parameters) on a desktop computer. We also describe a method for initial value estimation of the model parameters, which appears to favor identification of global optimum and can further reduce the computational cost. The PSO-GSS algorithm is applicable for kinetic models of arbitrary topology and size and compatible with common stimulation protocols, which provides a convenient approach for establishing kinetic models at the macroscopic level
An analysis of use and performance data aggregated from 35 institutional repositories
Purpose – This study demonstrates that aggregated data from the Repository Analytics and Metrics Portal (RAMP) have significant potential to analyze visibility and use of institutional repositories (IR) as well as potential factors affecting their use, including repository size, platform, content, device and global location. The RAMP dataset is unique and public.
Design/methodology/approach – The webometrics methodology was followed to aggregate and analyze use and performance data from 35 institutional repositories in seven countries that were registered with the RAMP for a five-month period in 2019. The RAMP aggregates Google Search Console (GSC) data to show IR items that surfaced in search results from all Google properties.
Findings – The analyses demonstrate large performance variances across IR as well as low overall use. The findings also show that device use affects search behavior, that different content types such as electronic thesis and dissertation (ETD) may affect use and that searches originating in the Global South show much higher use of mobile devices than in the Global North.
Research limitations/implications – The RAMP relies on GSC as its sole data source, resulting in somewhat conservative overall numbers. However, the data are also expected to be as robot free as can be hoped.
Originality/value – This may be the first analysis of aggregate use and performance data derived from a global set of IR, using an openly published dataset. RAMP data offer significant research potential with regard to quantifying and characterizing variances in the discoverability and use of IR content
Hybridizing the electromagnetism-like algorithm with descent search for solving engineering design problems
In this paper, we present a new stochastic hybrid technique for constrained global optimization. It is a combination of the electromagnetism-like (EM) mechanism with a random local search, which is a
derivative-free procedure with high ability of producing a descent direction. Since the original EM algorithm is specifically designed for solving bound constrained problems, the approach herein adopted for handling
the inequality constraints of the problem relies on selective conditions that impose a sufficient reduction either in the constraints violation or in the objective function value, when comparing two points at a time.
The hybrid EM method is tested on a set of benchmark engineering design problems and the numerical results demonstrate the effectiveness of the proposed approach. A comparison with results from other
stochastic methods is also included
Diversity of Decline-Rate-Corrected Type Ia Supernova Rise Times: One Mode or Two?
B-band light-curve rise times for eight unusually well-observed nearby Type
Ia supernovae (SNe) are fitted by a newly developed template-building
algorithm, using light-curve functions that are smooth, flexible, and free of
potential bias from externally derived templates and other prior assumptions.
From the available literature, photometric BVRI data collected over many
months, including the earliest points, are reconciled, combined, and fitted to
a unique time of explosion for each SN. On average, after they are corrected
for light-curve decline rate, three SNe rise in 18.81 +- 0.36 days, while five
SNe rise in 16.64 +- 0.21 days. If all eight SNe are sampled from a single
parent population (a hypothesis not favored by statistical tests), the rms
intrinsic scatter of the decline-rate-corrected SN rise time is 0.96 +0.52
-0.25 days -- a first measurement of this dispersion. The corresponding global
mean rise time is 17.44 +- 0.39 days, where the uncertainty is dominated by
intrinsic variance. This value is ~2 days shorter than two published averages
that nominally are twice as precise, though also based on small samples. When
comparing high-z to low-z SN luminosities for determining cosmological
parameters, bias can be introduced by use of a light-curve template with an
unrealistic rise time. If the period over which light curves are sampled
depends on z in a manner typical of current search and measurement strategies,
a two-day discrepancy in template rise time can bias the luminosity comparison
by ~0.03 magnitudes.Comment: As accepted by The Astrophysical Journal; 15 pages, 6 figures, 2
tables. Explanatory material rearranged and enhanced; Fig. 4 reformatte
Ad-hoc Limited Scale-Free Models for Unstructured Peer-to-Peer Networks
Several protocol efficiency metrics (e.g., scalability, search success rate,
routing reachability and stability) depend on the capability of preserving
structure even over the churn caused by the ad-hoc nodes joining or leaving the
network. Preserving the structure becomes more prohibitive due to the
distributed and potentially uncooperative nature of such networks, as in the
peer-to-peer (P2P) networks. Thus, most practical solutions involve
unstructured approaches while attempting to maintain the structure at various
levels of protocol stack. The primary focus of this paper is to investigate
construction and maintenance of scale-free topologies in a distributed manner
without requiring global topology information at the time when nodes join or
leave. We consider the uncooperative behavior of peers by limiting the number
of neighbors to a pre-defined hard cutoff value (i.e., no peer is a major hub),
and the ad-hoc behavior of peers by rewiring the neighbors of nodes leaving the
network. We also investigate the effect of these hard cutoffs and rewiring of
ad-hoc nodes on the P2P search efficiency.Comment: 10 pages, 6 figures, 43 references. Proceedings of The 8th IEEE
International Conference on Peer-to-Peer Computing 2008 (IEEE P2P 2008),
Aachen, German
TRAINING FOR THE UNIVERSAL MUSEUM
"TRAINING FOR THE UNIVERSAL MUSEUM" addresses a theme of our time. A Canadian, Marshall McLuhan, coined the phrase "global village" for this age which has witnessed mass travel, mass communications, even mass credit. Are we now about to see the "mass museum", a museum presumably homogenized and popularized for whatever constitutes the greatest cohort of global visitor which might arrive on the doorsteps of every-museum, every-where? The contributors to this volume think not. But there is in these papers some evidence of worry that we as individuals and institutions responsible for the education and professional development of museum workers are failing to consider seriously the impacts of the "global" forces at work in modern societies. Angelica Ruge discusses how the Germans are re-organizing museum training into a cohesive scheme, searching out the best elements from the former two states that now comprise the new German state. Margaret Greeves and Chris Newbery document the British search for a value free (and universally applicable?) set of museological skills which will underpin performance standards in the workplace. Both of these papers offer a response to the redefinition of the post-modern national state which as we watch, is redrawing political boundaries on every continent, and emphasizing the portability of skills and learning for the itinerant knowledge-industry worker.
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