Computational intelligence and neuroscience
May 21, 2020
In view of the weak generalization of traditional event recognition methods, the limitation of dependence on field knowledge of expert, the longer train time of deep neural network, and the problem of gradient dispersion, the neural network joint mod...
BACKGROUND: Cognitive impairment is common in patients with multiple sclerosis (MS). Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity.
Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are often uncomputable, or lack practical implementations. In this paper we a...
In this paper we probe the interaction between sequential and hierarchical learning by investigating implicit learning in a group of school-aged children. We administered a serial reaction time task, in the form of a modified Simon Task in which the ...
Neural networks : the official journal of the International Neural Network Society
May 7, 2020
Neural networks implemented with traditional hardware face inherent limitation of memory latency. Specifically, the processing units like GPUs, FPGAs, and customized ASICs, must wait for inputs to read from memory and outputs to write back. This moti...
In 1982, John Hopfield published a neural network model for memory retrieval, a model that became a cornerstone in theoretical neuroscience. In a recent paper, Krotov and Hopfield built on these early studies and showed how a network that incorporate...
Neural networks : the official journal of the International Neural Network Society
May 4, 2020
Humans live among other humans, not in isolation. Therefore, the ability to learn and behave in multi-agent environments is essential for any autonomous system that intends to interact with people. Due to the presence of multiple simultaneous learner...
Neural networks : the official journal of the International Neural Network Society
Apr 21, 2020
Currently, usual approaches for fast robot control are largely reliant on solving online optimal control problems. Such methods are known to be computationally intensive and sensitive to model accuracy. On the other hand, animals plan complex motor a...
Human learning is one of the main topics in psychology and cognitive neuroscience. The analysis of experimental data, e.g. from category learning experiments, is a major challenge due to confounding factors related to perceptual processing, feedback ...
Although more individuals are relying on information provided by nonhuman agents, such as artificial intelligence and robots, little research has examined how persuasion attempts made by nonhuman agents might differ from persuasion attempts made by h...