AIMC Topic: Learning

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BC-PMJRS: A Brain Computing-inspired Predefined Multimodal Joint Representation Spaces for enhanced cross-modal learning.

Neural networks : the official journal of the International Neural Network Society
Multimodal learning faces two key challenges: effectively fusing complex information from different modalities, and designing efficient mechanisms for cross-modal interactions. Inspired by neural plasticity and information processing principles in th...

A knowledge tracing approach with dual graph convolutional networks and positive/negative feature enhancement network.

PloS one
Knowledge tracing models predict students' mastery of specific knowledge points by analyzing their historical learning performance. However, existing methods struggle with handling a large number of skills, data sparsity, learning differences, and co...

Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing.

PloS one
In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing model (CL-PTKT...

Exploration and exploitation in continual learning.

Neural networks : the official journal of the International Neural Network Society
Continual learning (CL) has received a surge of interest, particularly in parameter isolation approaches, aiming to prevent catastrophic forgetting by assigning a disjoint parameter set to each task. Despite their effectiveness, existing approaches o...

A personalized recommendation algorithm for English exercises incorporating fuzzy cognitive models and multiple attention mechanisms.

Scientific reports
In the era of digital education, the rapid growth and disordered distribution of learning resources present new challenges for online learning. However, most of the exercise recommendation systems lack targeted guidance and personalization. In respon...

Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.

IEEE transactions on neural networks and learning systems
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectiv...

Curriculum is more influential than haptic feedback when learning object manipulation.

Science advances
Dexterous manipulation remains an aspirational goal for autonomous robotic systems, particularly when learning to lift and rotate objects against gravity with intermittent finger contacts. We use model-free reinforcement learning to compare the effec...

Mastering diverse control tasks through world models.

Nature
Developing a general algorithm that learns to solve tasks across a wide range of applications has been a fundamental challenge in artificial intelligence. Although current reinforcement-learning algorithms can be readily applied to tasks similar to w...

Enhancing target speaker extraction with Hierarchical Speaker Representation Learning.

Neural networks : the official journal of the International Neural Network Society
Target speaker extraction aims to obtain the speech of the specific speaker from a mixture of multiple voices. The conventional approach exploits the target speaker embeddings from a pre-recorded speech segment as auxiliary information, providing pri...

[How older people are learning through artificial intelligence-assisted health technologies : Cute seals and nervous fall sensors].

Zeitschrift fur Gerontologie und Geriatrie
BACKGROUND: With the growing use of artificial intelligence (AI) in various areas of life, AI technologies are increasingly being developed for the nursing and care of older people and are intended to contribute to greater safety for older people in ...