AIMC Journal:
Neural networks : the official journal of the International Neural Network Society

Showing 161 to 170 of 2842 articles

Low-Rank Representation with Empirical Kernel Space Embedding of Manifolds.

Neural networks : the official journal of the International Neural Network Society Jan 25, 2025
Low-Rank Representation (LRR) methods integrate low-rank constraints and projection operators to model the mapping from the sample space to low-dimensional manifolds. Nonetheless, existing approaches typically apply Euclidean algorithms directly to m...
Humans Neural Networks, Computer Machine Learning Algorithms
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Context Sensitive Network for weakly-supervised fine-grained temporal action localization.

Neural networks : the official journal of the International Neural Network Society Jan 24, 2025
Weakly-supervised fine-grained temporal action localization seeks to identify fine-grained action instances in untrimmed videos using only video-level labels. The primary challenge in this task arises from the subtle distinctions among various fine-g...
Humans Neural Networks, Computer Algorithms Time Factors Video Recording
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Combining various training and adaptation algorithms for ensemble few-shot classification.

Neural networks : the official journal of the International Neural Network Society Jan 24, 2025
To mitigate the shortage of labeled data, Few-Shot Classification (FSC) methods train deep neural networks (DNNs) on a base dataset with sufficient labeled data, and then adapt them to target tasks using a few labeled data. Despite notable progress, ...
Humans Neural Networks, Computer Algorithms Deep Learning
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Knowledge-Guided Semantically Consistent Contrastive Learning for sequential recommendation.

Neural networks : the official journal of the International Neural Network Society Jan 23, 2025
Contrastive learning has gained dominance in sequential recommendation due to its ability to derive self-supervised signals for addressing data sparsity problems. However, caused by random augmentations (e.g., crop, mask, and reorder), existing metho...
Humans Neural Networks, Computer Machine Learning Semantics Knowledge
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UNAGI: Unified neighbor-aware graph neural network for multi-view clustering.

Neural networks : the official journal of the International Neural Network Society Jan 23, 2025
Multi-view graph refining-based clustering (MGRC) methods aim to facilitate the clustering of data via Graph Neural Networks (GNNs) by learning optimal graphs that reflect the underlying topology of the data. However, current MGRC approaches are limi...
Humans Neural Networks, Computer Algorithms Cluster Analysis Graph Neural Networks
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SQGE: Support-query prototype guidance and enhancement for few-shot relational triple extraction.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
The current few-shot relational triple extraction (FS-RTE) techniques, which rely on prototype networks, have made significant progress. Nevertheless, the scarcity of data in the support set results in both intra-class and inter-class gaps in FS-RTE....
Neural Networks, Computer Algorithms
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SAC-BL: A hypothesis testing framework for unsupervised visual anomaly detection and location.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Reconstruction-based methods achieve promising performance for visual anomaly detection (AD), relying on the underlying assumption that the anomalies cannot be accurately reconstructed. However, this assumption does not always hold, especially when s...
Humans Neural Networks, Computer Algorithms Unsupervised Machine Learning
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EHM: Exploring dynamic alignment and hierarchical clustering in unsupervised domain adaptation via high-order moment-guided contrastive learning.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Unsupervised domain adaptation (UDA) aims to annotate unlabeled target domain samples using transferable knowledge learned from the labeled source domain. Optimal transport (OT) is a widely adopted probability metric in transfer learning for quantify...
Humans Neural Networks, Computer Algorithms Cluster Analysis Unsupervised Machine Learning
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A multi-agent reinforcement learning framework for cross-domain sequential recommendation.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Sequential recommendation models aim to predict the next item based on the sequence of items users interact with, ordered chronologically. However, these models face the challenge of data sparsity. Recent studies have explored cross-domain sequential...
Humans Neural Networks, Computer Reinforcement, Psychology
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Online ensemble model compression for nonstationary data stream learning.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Learning from data streams that emerge from nonstationary environments has many real-world applications and poses various challenges. A key characteristic of such a task is the varying nature of the underlying data distributions over time (concept dr...
Humans Neural Networks, Computer Machine Learning Algorithms Learning Data Compression Online Systems
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