391 research outputs found
Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks
When constructing models that learn from noisy labels produced by multiple
annotators, it is important to accurately estimate the reliability of
annotators. Annotators may provide labels of inconsistent quality due to their
varying expertise and reliability in a domain. Previous studies have mostly
focused on estimating each annotator's overall reliability on the entire
annotation task. However, in practice, the reliability of an annotator may
depend on each specific instance. Only a limited number of studies have
investigated modelling per-instance reliability and these only considered
binary labels. In this paper, we propose an unsupervised model which can handle
both binary and multi-class labels. It can automatically estimate the
per-instance reliability of each annotator and the correct label for each
instance. We specify our model as a probabilistic model which incorporates
neural networks to model the dependency between latent variables and instances.
For evaluation, the proposed method is applied to both synthetic and real data,
including two labelling tasks: text classification and textual entailment.
Experimental results demonstrate our novel method can not only accurately
estimate the reliability of annotators across different instances, but also
achieve superior performance in predicting the correct labels and detecting the
least reliable annotators compared to state-of-the-art baselines.Comment: 9 pages, 1 figures, 10 tables, 2019 Annual Conference of the North
American Chapter of the Association for Computational Linguistics (NAACL2019
Spin fluctuations and charge properties of core shell C+M (V, Mn, Cr, Ni, Co)
Transition metal clusters have a broad spectrum of potential applications in
electronic and magnetic devices owing to their unique properties. Protective
shells such as fullerene C can be introduced to improve their stability.
In this study, we optimized five core shell structures, C+M (V,
Mn, Cr, Ni, Co), and calculated their electromagnetic properties using density
functional theory.We determined that there is electron transfer between
C and the transition metal clusters near the Fermi surface, and that the
d orbitals contribute most to the magnetism of the structure.
C+Ni was antiferromagnetic. The magnetic properties of the
clusters were significantly altered, revealing antiferromagnetism. The results
establish a theoretical starting point for tuning the electronic and magnetic
properties of 13-atom clusters embedded in fullerene cages
Bond relaxation, electronic and magnetic behavior of 2D metals structures Y on Li(110) surface
We investigated the bond, electronic and magnetic behavior of adsorption
Yttrium atoms on Lithium (110) surface using a combination of
Bond-order-length-strength(BOLS) correlation and density-functional
theory(DFT). We found that adsorption Y atoms on Li(110) surfaces form
two-dimensional (2D) geometric structures of hexagon, nonagon, solid hexagonal,
quadrangle and triangle. The consistent with the magnetic moment are
6.66{\mu}B, 5.54{\mu}B, 0.28{\mu}B, 1.04{\mu}B, 2.81{\mu}B, respectively. In
addition, this work could pave the way for design new 2D metals electronic and
magnetic properties
Dynamic analysis and optimal control of a novel fractional-order 2I2SR rumor spreading model
In this paper, a novel fractional-order 2I2SR rumor spreading model is investigated. Firstly, the boundedness and uniqueness of solutions are proved. Then the next-generation matrix method is used to calculate the threshold. Furthermore, the stability of rumor-free/spreading equilibrium is discussed based on fractional-order Routh–Hurwitz stability criterion, Lyapunov function method, and invariance principle. Next, the necessary conditions for fractional optimal control are obtained. Finally, some numerical simulations are given to verify the results
Semi-wave and spreading speed of the nonlocal Fisher-KPP equation with free boundaries
In Cao, Du, Li and Li [8], a nonlocal diffusion model with free boundaries
extending the local diffusion model of Du and Lin [12] was introduced and
studied. For Fisher-KPP type nonlinearities, its long-time dynamical behaviour
is shown to follow a spreading-vanishing dichotomy. However, when spreading
happens, the question of spreading speed was left open in [8]. In this paper we
obtain a rather complete answer to this question. We find a condition on the
kernel function such that spreading grows linearly in time exactly when this
condition holds, which is achieved by completely solving the associated
semi-wave problem that determines this linear speed; when the kernel function
violates this condition, we show that accelerating spreading happens
Hierarchical Modes Exploring in Generative Adversarial Networks
In conditional Generative Adversarial Networks (cGANs), when two different
initial noises are concatenated with the same conditional information, the
distance between their outputs is relatively smaller, which makes minor modes
likely to collapse into large modes. To prevent this happen, we proposed a
hierarchical mode exploring method to alleviate mode collapse in cGANs by
introducing a diversity measurement into the objective function as the
regularization term. We also introduced the Expected Ratios of Expansion (ERE)
into the regularization term, by minimizing the sum of differences between the
real change of distance and ERE, we can control the diversity of generated
images w.r.t specific-level features. We validated the proposed algorithm on
four conditional image synthesis tasks including categorical generation, paired
and un-paired image translation and text-to-image generation. Both qualitative
and quantitative results show that the proposed method is effective in
alleviating the mode collapse problem in cGANs, and can control the diversity
of output images w.r.t specific-level features
Topological Bonding and Electronic properties of CdTe semiconductor material with microporous structure
CdTe is II-VI semiconductor material with excellent characteristics and has
demonstrated promising potential for application in the photovoltaic field. The
electronic properties of Cd43Te28 with microporous structures have been
investigated based on density functional theory. The newly established
binding-energy and bond-charge model have been used to convert the value of
Hamiltonian into bonding values. We provide a method for describing topological
chemical bonds by atomic coordinates and wave phases. We also discuss the
dynamic process of the wave function with time and the magic cube matrix. This
study provides an innovative method and technology for the accurate analysis of
the topological bonding and electronic properties of microporous semiconductor
materials
Electronic structure and bond relaxation at Na/Ta(110) interfaces and 1D-chain and 2D-ring Ta metal structures on Na(110)
We investigated the mechanism of Na/Ta(110) and Ta/Na(110) interfaces using a
combination of bond band barrier (BBB) and zone selective electron spectroscopy
(ZES) correlation. We found that 7/9 ML and 8/9 ML Ta metal on a Na(110)
surface form one dimensional (1D) chain and two dimensional (2D) ring
structures, respectively. Moreover, we show that on Na(110), the Ta-induced
Na(110) surface binding energy (BE) shifts are dominated by quantum entrapment.
On the contrary, on a Ta(110) surface, the Na-induced Ta(110) surface BE shifts
are dominated by polarization. Thus, the BBB and ZES strategy could potentially
be used for designing 1D and 2D metals with desired structures and properties
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