8,254 research outputs found
Compositional Morphology for Word Representations and Language Modelling
This paper presents a scalable method for integrating compositional
morphological representations into a vector-based probabilistic language model.
Our approach is evaluated in the context of log-bilinear language models,
rendered suitably efficient for implementation inside a machine translation
decoder by factoring the vocabulary. We perform both intrinsic and extrinsic
evaluations, presenting results on a range of languages which demonstrate that
our model learns morphological representations that both perform well on word
similarity tasks and lead to substantial reductions in perplexity. When used
for translation into morphologically rich languages with large vocabularies,
our models obtain improvements of up to 1.2 BLEU points relative to a baseline
system using back-off n-gram models.Comment: Proceedings of the 31st International Conference on Machine Learning
(ICML
Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent
Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain–body– environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour
A test of arm-induced star formation in spiral galaxies from near-IR and H imaging
We have imaged a sample of 20 spiral galaxies in H and in the
near-infrared K band (2.2 um), in order to determine the location and strength
of star formation in these objects with respect to perturbations in the old
stellar population. We have found that star formation rates are significantly
enhanced in the vicinity of K band arms. We have also found that this
enhancement in star formation rate in arm regions correlates well with a
quantity that measures the relative strengths of shocks in arms. Assuming that
the K band light is dominated by emission from the old stellar population, this
shows that density waves trigger star formation in the vicinity of spiral arms.Comment: 6 pages, 1 figure, accpeted for publication in MNRA
Interactions Between Charged Rods Near Salty Surfaces
Using both theoretical modeling and computer simulations we study a model
system for DNA interactions in the vicinity of charged membranes. We focus on
the polarization of the mobile charges in the membranes due to the nearby
charged rods (DNA) and the resulting screening of their fields and inter-rod
interactions. We find, both within a Debye-Huckel model and in Brownian
dynamics simulations, that the confinement of the mobile charges to the surface
leads to a qualitative reduction in their ability to screen the charged rods to
the degree that the fields and resulting interactions are not finite-ranged as
in systems including a bulk salt concentration, but rather decay algebraically
and the screening effect is more like an effective increase in the multipole
moment of the charged rod
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