311 research outputs found
Breaking the Architecture Barrier: A Method for Efficient Knowledge Transfer Across Networks
Transfer learning is a popular technique for improving the performance of
neural networks. However, existing methods are limited to transferring
parameters between networks with same architectures. We present a method for
transferring parameters between neural networks with different architectures.
Our method, called DPIAT, uses dynamic programming to match blocks and layers
between architectures and transfer parameters efficiently. Compared to existing
parameter prediction and random initialization methods, it significantly
improves training efficiency and validation accuracy. In experiments on
ImageNet, our method improved validation accuracy by an average of 1.6 times
after 50 epochs of training. DPIAT allows both researchers and neural
architecture search systems to modify trained networks and reuse knowledge,
avoiding the need for retraining from scratch. We also introduce a network
architecture similarity measure, enabling users to choose the best source
network without any training.Comment: 23 pages, 16 figure
Chaos Machine: Different Approach to the Application and Significance of Numbers
In this paper we describe a theoretical model of \underline{chaos machine}, which combines the benefits of hash function and pseudo-random function, forming flexible \textit{one-way} \underline{push-pull interface}. It presents the idea to create a universal tool (design pattern) with modular design and customizable parameters, that can be applied where \textit{randomness} and \textit{sensitiveness} is needed (random oracle), and where appropriate construction determines case of application and selection of parameters provides preferred properties and security level. Machine can be used to implement many cryptographic primitives, including cryptographic hashes, message authentication codes and pseudo-random number generators.
Additionally, document includes sample implementation of chaos machine named Naive Czyzewski Generator, abbreviated NCG, that passes all the Dieharder, NIST and TestU01 test sets. Algorithm was designed and evaluated to be a cryptographically strong, inasmuch as indistinguishable from a uniform random function. The generator was developed to work as cryptographically secure pseudo-random number generator, collision resistance hash function or a cryptographic module. One can target a given period length by choosing the appropriate space parameter, i.e., for a given parameter , algorithm is claimed to have period between to
Nuclear Attenuation of high energy two-hadron system in the string model
Nuclear attenuation of the two-hadron system is considered in the string
model. The two-scale model and its improved version with two different choices
of constituent formation time and sets of parameters obtained earlier for the
single hadron attenuation, are used to describe available experimental data for
the -dependence of subleading hadron, whereas satisfactory agreement with
the experimental data has been observed. A model prediction for
-dependence of the nuclear attenuation of the two-hadron system is also
presented.Comment: 8 page
Hadron production in deep inelastic lepton-nucleus scattering
Predictions for semi-inclusive deep inelastic lepton-nucleus scattering are
presented. Both the effects of gluon radiation by the struck quark and the
absorption of the produced hadron are considered. The gluon radiation covers a
larger window in virtuality because of the increased deconfinement of
quarks inside nuclei. The absorption of hadrons formed inside the nucleus is
described with a flavor dependent cross section. Calculations for rescaled
fragmentation functions and nuclear absorption are compared with the EMC and
HERMES data for N, Cu and Kr targets with respect to the deuteron target.
Predictions for Ne and Xe targets in the HERMES kinematic regime are given.Comment: 27 pages, 12 figures. Section 2 on rescaling modified. Extended
discussion of the results in Sec. 5 and 6. To be published in Nucl.Phys.
The impact of pulsed electric field on the extraction of bioactive compounds from beetroot
Beetroot is a root vegetable rich in different bioactive components, such as vitamins, minerals, phenolics, carotenoids, nitrate, ascorbic acids, and betalains, that can have a positive effect on human health. The aim of this work was to study the influence of the pulsed electric field (PEF) at different electric field strengths (4.38 and 6.25 kV/cm), pulse number 10\u201330, and energy input 0\u201312.5 kJ/kg as a pretreatment method on the extraction of betalains from beetroot. The obtained results showed that the application of PEF pre-treatment significantly (p < 0.05) influenced the efficiency of extraction of bioactive compounds from beetroot. The highest increase in the content of betalain compounds in the red beet\u2019s extract (betanin by 329%, vulgaxanthin by 244%, compared to the control sample), was noted for 20 pulses of electric field at 4.38 kV/cm of strength. Treatment of the plant material with a PEF also resulted in an increase in the electrical conductivity compared to the non-treated sample due to the increase in cell membrane permeability, which was associated with leakage of substances able to conduct electricity, including mineral salts, into the intercellular space
A global reanalysis of nuclear parton distribution functions
We determine the nuclear modifications of parton distribution functions of
bound protons at scales GeV and momentum fractions
in a global analysis which utilizes nuclear hard process
data, sum rules and leading-order DGLAP scale evolution. The main improvements
over our earlier work {\em EKS98} are the automated minimization,
simplified and better controllable fit functions, and most importantly, the
possibility for error estimates. The resulting 16-parameter fit to the N=514
datapoints is good, . Within the error estimates
obtained, the old {\em EKS98} parametrization is found to be fully consistent
with the present analysis, with no essential difference in terms of
either. We also determine separate uncertainty bands for the nuclear gluon and
sea quark modifications in the large- region where they are not stringently
constrained by the available data. Comparison with other global analyses is
shown and uncertainties demonstrated. Finally, we show that RHIC-BRAHMS data
for inclusive hadron production in d+Au collisions lend support for a stronger
gluon shadowing at and also that fairly large changes in the gluon
modifications do not rapidly deteriorate the goodness of the overall fits, as
long as the initial gluon modifications in the region remain
small.Comment: 33 pages, 14 figure
Atomic Mass Dependence of Hadron Production in Deep Inelastic Scattering on Nuclei
Hadron production in lepton-nucleus deep inelastic scattering is studied in
an absorption model. In the proposed model, the early stage of hadronization in
the nuclear medium is dominated by prehadron formation and absorption,
controlled by flavor-dependent formation lengths and absorption cross sections.
Computations for hadron multiplicity ratios are presented and compared with the
HERMES experimental data for pions, kaons, protons and antiprotons. The
mass-number dependence of hadron attenuation is shown to be sensitive to the
underlying hadronization dynamics. Contrary to common expectations for
absorption models, a leading term proportional to A^{2/3} is found. Deviations
from the leading behavior arise at large mass-numbers and large hadron
fractional momenta.Comment: 30 pages, 10 figures, v2: minor changes (legend in figs 5 & 6 is
added), v3: additional explanations are added, v4: Version combines v3 and
the erratum hep-ph/050803
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