18,869 research outputs found
Deep Multiple Description Coding by Learning Scalar Quantization
In this paper, we propose a deep multiple description coding framework, whose
quantizers are adaptively learned via the minimization of multiple description
compressive loss. Firstly, our framework is built upon auto-encoder networks,
which have multiple description multi-scale dilated encoder network and
multiple description decoder networks. Secondly, two entropy estimation
networks are learned to estimate the informative amounts of the quantized
tensors, which can further supervise the learning of multiple description
encoder network to represent the input image delicately. Thirdly, a pair of
scalar quantizers accompanied by two importance-indicator maps is automatically
learned in an end-to-end self-supervised way. Finally, multiple description
structural dissimilarity distance loss is imposed on multiple description
decoded images in pixel domain for diversified multiple description generations
rather than on feature tensors in feature domain, in addition to multiple
description reconstruction loss. Through testing on two commonly used datasets,
it is verified that our method is beyond several state-of-the-art multiple
description coding approaches in terms of coding efficiency.Comment: 8 pages, 4 figures. (DCC 2019: Data Compression Conference). Testing
datasets for "Deep Optimized Multiple Description Image Coding via Scalar
Quantization Learning" can be found in the website of
https://github.com/mdcnn/Deep-Multiple-Description-Codin
FIML estimation of a bivariate probit selection rule: an application on firm growth and subsidisation
This study applies a full information maximum likelihood (FIML) estimator of the sample selection model with bivariate selection rule for the investigation of the impact of subsidised firm foundation from unemployment on employment growth of the firm. The empirical analysis is based on the ZEW Firm Start-up Panel using a cohort of firms founded in 15 labour market districts during 1993 and 1995. Estimation results show that the use of the FIML estimator is clearly warranted, compared to a two-step estimator. The FIML model yields a significant negative impact of bridging allowance on employment growth, whereas the two-step estimator underestimates the impact. --
Dynamic Pooling for the Combination of Forecasts Generated Using Multi Level Learning
In this paper we provide experimental results and
extensions to our previous theoretical findings concerning the
combination of forecasts that have been diversified by three
different methods: with parameters learned at different data
aggregation levels, by thick modeling and by the use of different
forecasting methods. An approach of error variance based
pooling as proposed by Aiolfi and Timmermann has been compared
with flat combinations as well as an alternative pooling
approach in which we consider information about the used
diversification. An advantage of our approach is that it leads to
the generation of novel multi step multi level forecast generation
structures that carry out the combination in different steps of
pooling corresponding to the different types of diversification.
We describe different evolutionary approaches in order to
evolve the order of pooling of the diversification dimensions.
Extensions of such evolutions allow the generation of more
flexible multi level multi step combination structures containing
better adaptive capabilities. We could prove a significant error
reduction comparing results of our generated combination
structures with results generated with the algorithm of Aiolfi
and Timmermann as well as with flat combination for the
application of Revenue Management seasonal forecasting
Parametric Estimation of Handoff
The efficiency of wireless technology depends upon the seamless connectivity
to the user at anywhere any time.Heterogeneous wireless networks are an
integration of different networks with diversified technologies. The most
essential requirement for Seamless vertical handover is that the received
signal strength should always be healthy. Mobile device enabled with multiple
wireless technologies makes it possible to maintain seamless connectivity in
highly dynamic environment.Since the available bandwidth is limited and the
number of users is growing rapidly, it is a real challenge to maintain the
received signal strength in a healthy stage.In this work, the proposed, cost
effective parametric estimation for vertical handover shows that the received
signal strength maintains a healthy level by considering the novel concept.Comment: 5 Pages,3 figures, NCCCS-12,ISBN:978-1-4673-2837-
Industry diversity, competition and firm relatedness: The impact on employment before and after the 2008 global financial crisis
Industry diversity, competition and firm relatedness: the impact on employment before and after the 2008 global financial crisis. Regional Studies. This study investigates the extent to which indicators of external-scale economies impacted employment growth in Canada over the period 2004–11. It focuses on knowledge spillovers between firms while accounting for Marshallian specialization, Jacobs’ diversity and competition by industry, as well as related and unrelated firm varieties in terms of employment and sales. It is found that the employment growth effects of local competition and diversity are positive, while the effect of Marshallian specialization is negative. Diversification is found to be particularly important for employment growth during the global financial crisis and immediately thereafter
Performance Limits and Geometric Properties of Array Localization
Location-aware networks are of great importance and interest in both civil
and military applications. This paper determines the localization accuracy of
an agent, which is equipped with an antenna array and localizes itself using
wireless measurements with anchor nodes, in a far-field environment. In view of
the Cram\'er-Rao bound, we first derive the localization information for static
scenarios and demonstrate that such information is a weighed sum of Fisher
information matrices from each anchor-antenna measurement pair. Each matrix can
be further decomposed into two parts: a distance part with intensity
proportional to the squared baseband effective bandwidth of the transmitted
signal and a direction part with intensity associated with the normalized
anchor-antenna visual angle. Moreover, in dynamic scenarios, we show that the
Doppler shift contributes additional direction information, with intensity
determined by the agent velocity and the root mean squared time duration of the
transmitted signal. In addition, two measures are proposed to evaluate the
localization performance of wireless networks with different anchor-agent and
array-antenna geometries, and both formulae and simulations are provided for
typical anchor deployments and antenna arrays.Comment: to appear in IEEE Transactions on Information Theor
Maximize Resolution or Minimize Error? Using Genotyping-By-Sequencing to Investigate the Recent Diversification of Helianthemum (Cistaceae)
A robust phylogenetic framework, in terms of extensive geographical and taxonomic sampling, well-resolved species relationships and high certainty of tree topologies and branch length estimations, is critical in the study of macroevolutionary patterns. Whereas Sanger sequencing-based methods usually recover insufficient phylogenetic signal, especially in recently diversified lineages, reduced-representation sequencing methods tend to provide well-supported phylogenetic relationships, but usually entail remarkable bioinformatic challenges due to the inherent trade-off between the number of SNPs and the magnitude of associated error rates. The genus Helianthemum (Cistaceae) is a species-rich and taxonomically complex Palearctic group of plants that diversified mainly since the Upper Miocene. It is a challenging case study since previous attempts using Sanger sequencing were unable to resolve the intrageneric phylogenetic relationships. Aiming to obtain a robust phylogenetic reconstruction based on genotyping-by-sequencing (GBS), we established a rigorous methodological workflow in which we i) explored how variable settings during dataset assembly have an impact on error rates and on the degree of resolution under concatenation and coalescent approaches, ii) assessed the effect of two extreme parameter configurations (minimizing error rates vs. maximizing phylogenetic resolution) on tree topology and branch lengths, and iii) evaluated the effects of these two configurations on estimates of divergence times and diversification rates. Our analyses produced highly supported topologically congruent phylogenetic trees for both configurations. However, minimizing error rates did produce more reliable branch lengths, critically affecting the accuracy of downstream analyses (i.e. divergence times and diversification rates). In addition to recommending a revision of intrageneric systematics, our results enabled us to identify three highly diversified lineages in Helianthemum in contrasting geographical areas and ecological conditions, which started radiating in the Upper Miocene.España, MINECO grants CGL2014- 52459-P and CGL2017-82465-PEspaña, Ministerio de Economía, Industria y Competitividad, reference IJCI-2015-2345
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