AI Medical Compendium Topic:
Learning

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A complementary learning systems approach to temporal difference learning.

Neural networks : the official journal of the International Neural Network Society
Complementary Learning Systems (CLS) theory suggests that the brain uses a 'neocortical' and a 'hippocampal' learning system to achieve complex behaviour. These two systems are complementary in that the 'neocortical' system relies on slow learning of...

A review of learning in biologically plausible spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Artificial neural networks have been used as a powerful processing tool in various areas such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has encouraged researchers to improve artificial neural networks by ...

Stable memory with unstable synapses.

Nature communications
What is the physiological basis of long-term memory? The prevailing view in Neuroscience attributes changes in synaptic efficacy to memory acquisition, implying that stable memories correspond to stable connectivity patterns. However, an increasing b...

Gated spiking neural network using Iterative Free-Energy Optimization and rank-order coding for structure learning in memory sequences (INFERNO GATE).

Neural networks : the official journal of the International Neural Network Society
We present a framework based on iterative free-energy optimization with spiking neural networks for modeling the fronto-striatal system (PFC-BG) for the generation and recall of audio memory sequences. In line with neuroimaging studies carried out in...

Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning.

Neural computation
Humans are able to master a variety of knowledge and skills with ongoing learning. By contrast, dramatic performance degradation is observed when new tasks are added to an existing neural network model. This phenomenon, termed , is one of the major r...

Neural Classification of Compost Maturity by Means of the Artificial Neural Network and Algorithm.

International journal of environmental research and public health
neural models and the algorithm were used to produce a classifier identifying the quality classes of compost, according to the degree of its maturation within a period of time recorded in digital images. Digital images of compost at different stage...

An approach on the implementation of full batch, online and mini-batch learning on a Mamdani based neuro-fuzzy system with center-of-sets defuzzification: Analysis and evaluation about its functionality, performance, and behavior.

PloS one
Due to the rapid technological evolution and communications accessibility, data generated from different sources of information show an exponential growth behavior. That is, volume of data samples that need to be analyzed are getting larger, so the m...

Multiclass heterogeneous domain adaptation via bidirectional ECOC projection.

Neural networks : the official journal of the International Neural Network Society
Heterogeneous domain adaptation aims to exploit the source domain data to train a prediction model for the target domain with different input feature space. Current methods either map the data points from different domains with different feature spac...

A critique of pure learning and what artificial neural networks can learn from animal brains.

Nature communications
Artificial neural networks (ANNs) have undergone a revolution, catalyzed by better supervised learning algorithms. However, in stark contrast to young animals (including humans), training such networks requires enormous numbers of labeled examples, l...

A two-route CNN model for bank account classification with heterogeneous data.

PloS one
Classifying bank accounts by using transaction data is encouraging in cracking down on illegal financial activities. However, few research simultaneously use heterogenous features, which are embedded in the time series data. In this paper, a two rout...