AIMC Topic: Learning

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Human-robot collaborative task planning using anticipatory brain responses.

PloS one Jul 11, 2023
Human-robot interaction (HRI) describes scenarios in which both human and robot work as partners, sharing the same environment or complementing each other on a joint task. HRI is characterized by the need for high adaptability and flexibility of robo...
Humans Algorithms Brain Computer Simulation Learning Robotics
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Tackling higher-order relations and heterogeneity: Dynamic heterogeneous hypergraph network for spatiotemporal activity prediction.

Neural networks : the official journal of the International Neural Network Society Jul 10, 2023
Spatiotemporal activity prediction aims to predict user activities at a particular time and location, which is applicable in city planning, activity recommendations, and other domains. The fundamental endeavor in spatiotemporal activity prediction is...
Neural Networks, Computer Learning
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Optimization of neural-network model using a meta-heuristic algorithm for the estimation of dynamic Poisson's ratio of selected rock types.

Scientific reports Jul 8, 2023
This research focuses on the predictive modeling between rocks' dynamic properties and the optimization of neural network models. For this purpose, the rocks' dynamic properties were measured in terms of quality factor (Q), resonance frequency (FR), ...
Neural Networks, Computer Algorithms Learning Neurons Heuristics
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Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis.

PLoS computational biology Jul 7, 2023
Many complex diseases share common genetic determinants and are comorbid in a population. We hypothesized that the co-occurrences of diseases and their overlapping genetic etiology can be exploited to simultaneously improve multiple diseases' polygen...
Humans Neural Networks, Computer Learning Risk Factors Genetic Predisposition to Disease Polymorphism, Single Nucleotide Multifactorial Inheritance
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Research on Intelligent English Education Based on the Short Video Recommendation Algorithm.

Computational intelligence and neuroscience Jul 7, 2023
In order to solve the problems of English education in the form of a short video, a research method of English intelligent education based on a short video recommendation algorithm was proposed. The recommendation system is a branch of artificial int...
Artificial Intelligence Algorithms Learning Intelligence Data Mining
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A survey on neural-symbolic learning systems.

Neural networks : the official journal of the International Neural Network Society Jul 6, 2023
In recent years, neural systems have demonstrated highly effective learning ability and superior perception intelligence. However, they have been found to lack effective reasoning and cognitive ability. On the other hand, symbolic systems exhibit exc...
Neural Networks, Computer Artificial Intelligence Learning Cognition Problem Solving
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Attribute Augmented Network Embedding Based on Generative Adversarial Nets.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Network embedding is to learn low-dimensional representations of nodes while preserving necessary information for network analysis tasks. Though representations preserving both structure and attribute features have achieved in many real-world applica...
Neural Networks, Computer Algorithms Learning
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Looking at Boundary: Siamese Densely Cooperative Fusion for Salient Object Detection.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Though deep learning-based saliency detection methods have achieved gratifying performance recently, the predicted saliency maps still suffer from the boundary challenge. From the perspective of foreground-background separation, this article attempts...
Neural Networks, Computer Learning Benchmarking
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Optimal Tracking in Switched Systems With Free Final Time and Fixed Mode Sequence Using Approximate Dynamic Programming.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Optimal tracking in switched systems with fixed mode sequence and free final time is studied in this article. In the optimal control problem formulation, the switching times and the final time are treated as parameters. For solving the optimal contro...
Neural Networks, Computer Learning
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Multi-Constraint Latent Representation Learning for Prognosis Analysis Using Multi-Modal Data.

IEEE transactions on neural networks and learning systems Jul 6, 2023
The Cox proportional hazard model has been widely applied to cancer prognosis prediction. Nowadays, multi-modal data, such as histopathological images and gene data, have advanced this field by providing histologic phenotype and genotype information....
Neural Networks, Computer Prognosis Learning Probability Generalization, Psychological
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