AIMC Topic: Learning

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Graph Transformer Networks: Learning meta-path graphs to improve GNNs.

Neural networks : the official journal of the International Neural Network Society Jun 4, 2022
Graph Neural Networks (GNNs) have been widely applied to various fields due to their powerful representations of graph-structured data. Despite the success of GNNs, most existing GNNs are designed to learn node representations on the fixed and homoge...
Neural Networks, Computer Learning Semantics
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Zero-Shot Deep Domain Adaptation With Common Representation Learning.

IEEE transactions on pattern analysis and machine intelligence Jun 3, 2022
Domain Adaptation aims at adapting the knowledge learned from a domain (source-domain) to another (target-domain). Existing approaches typically require a portion of task-relevant target-domain data a priori. We propose an approach, zero-shot deep do...
Machine Learning Algorithms Learning
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APANet: Auto-Path Aggregation for Future Instance Segmentation Prediction.

IEEE transactions on pattern analysis and machine intelligence Jun 3, 2022
Despite the remarkable progress achieved in conventional instance segmentation, the problem of predicting instance segmentation results for unobserved future frames remains challenging due to the unobservability of future data. Existing methods mainl...
Neural Networks, Computer Algorithms Learning Image Processing, Computer-Assisted
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Adaptive Contrastive Learning with Label Consistency for Source Data Free Unsupervised Domain Adaptation.

Sensors (Basel, Switzerland) Jun 2, 2022
Unsupervised domain adaptation, which aims to alleviate the domain shift between source domain and target domain, has attracted extensive research interest; however, this is unlikely in practical application scenarios, which may be due to privacy iss...
Machine Learning Learning Cluster Analysis Acclimatization
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A Path-Planning Approach Based on Potential and Dynamic Q-Learning for Mobile Robots in Unknown Environment.

Computational intelligence and neuroscience Jun 2, 2022
The path-planning approach plays an important role in determining how long the mobile robots can travel. To solve the path-planning problem of mobile robots in an unknown environment, a potential and dynamic Q-learning (PDQL) approach is proposed, wh...
Algorithms Computer Simulation Learning Robotics
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Deep Graph Learning for Anomalous Citation Detection.

IEEE transactions on neural networks and learning systems Jun 1, 2022
Anomaly detection is one of the most active research areas in various critical domains, such as healthcare, fintech, and public security. However, little attention has been paid to scholarly data, that is, anomaly detection in a citation network. Cit...
Neural Networks, Computer Algorithms Learning Data Mining Semantics
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Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning.

IEEE transactions on neural networks and learning systems Jun 1, 2022
Anomaly detection is an important data mining task with numerous applications, such as intrusion detection, credit card fraud detection, and video surveillance. However, given a specific complicated task with complicated data, the process of building...
Humans Neural Networks, Computer Machine Learning Learning Exploratory Behavior Imitative Behavior
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Semisupervised Training of Deep Generative Models for High-Dimensional Anomaly Detection.

IEEE transactions on neural networks and learning systems Jun 1, 2022
Abnormal behaviors in industrial systems may be early warnings on critical events that may cause severe damages to facilities and security. Thus, it is important to detect abnormal behaviors accurately and timely. However, the anomaly detection probl...
Neural Networks, Computer Learning Supervised Machine Learning
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Study on the Design and Optimization of Learning Environment Based on Artificial Intelligence and Virtual Reality Technology.

Computational intelligence and neuroscience May 31, 2022
More than half of the universities have recently added advanced technical courses for their students. The specialised courses would be the backbone to keep the students' knowledge updated. In that case, artificial intelligence (AI) and virtual realit...
Humans Artificial Intelligence Computers Technology Learning Virtual Reality
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Analysis of the Effect of Artificial Intelligence on Role Cognition in the Education System.

Occupational therapy international May 30, 2022
Taking the entire education system in Taiyuan City, Shanxi Province, Central China, as an example, this paper uses the questionnaire survey method to analyze the effect of artificial intelligence (AI) on role cognition in the education system. The ed...
Humans Artificial Intelligence Learning Adult Students Child, Preschool Cognition Occupational Therapy
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