35 research outputs found
Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits
Understanding how biological neural networks carry out learning using
spike-based local plasticity mechanisms can lead to the development of
powerful, energy-efficient, and adaptive neuromorphic processing systems. A
large number of spike-based learning models have recently been proposed
following different approaches. However, it is difficult to assess if and how
they could be mapped onto neuromorphic hardware, and to compare their features
and ease of implementation. To this end, in this survey, we provide a
comprehensive overview of representative brain-inspired synaptic plasticity
models and mixed-signal CMOS neuromorphic circuits within a unified framework.
We review historical, bottom-up, and top-down approaches to modeling synaptic
plasticity, and we identify computational primitives that can support
low-latency and low-power hardware implementations of spike-based learning
rules. We provide a common definition of a locality principle based on pre- and
post-synaptic neuron information, which we propose as a fundamental requirement
for physical implementations of synaptic plasticity. Based on this principle,
we compare the properties of these models within the same framework, and
describe the mixed-signal electronic circuits that implement their computing
primitives, pointing out how these building blocks enable efficient on-chip and
online learning in neuromorphic processing systems
Mapping 123 million neonatal, infant and child deaths between 2000 and 2017
Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations
EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020
Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)