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Downlink channel estimation for millimeter wave communication combining low-rank and sparse structure characteristics
The acquisition of channel state information (CSI) is essential in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. The mmWave...
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The Study of Image Completion Technique Using Low-Rank Concept in Matrix and Tensor Domain
In this paper, our interest is to solve the problem of image completion from degraded or noisy image with lost samples utilizing the concept of...
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Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications
Knowledge Graph (KG) has attracted more and more companies’ attention for its ability to connect different types of data in meaningful ways and...
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Deep data representation with feature propagation for semi-supervised learning
Graph-based embedding has attracted much attention in the fields of machine learning and pattern recognition. It is becoming an indispensable tool...
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Robust unsupervised feature selection via dual space latent representation learning and adaptive structure learning
Great significance has been attached to unsupervised feature selection in consideration of the difficulty in obtaining labels. Existent unsupervised...
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Reduction AWGN from Digital Images Using a New Local Optimal Low-Rank Approximation Method
In this paper, image noise reduction has been formulated as an optimization problem. The target image is denoised using a low-rank approximation of a...
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A Graph Representation Learning Framework Predicting Potential Multivariate Interactions
Link prediction is a widely adopted method for extracting valuable data insights from graphs, primarily aimed at predicting interactions between two...
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Partial label learning via low-rank representation and label propagation
In partial label learning, each training instance is assigned with a set of candidate labels, among which only one is correct. An intuitive strategy...
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CoDF-Net: coordinated-representation decision fusion network for emotion recognition with EEG and eye movement signals
Physiological signals, such as EEG and eye movements, have emerged as promising research topics in emotion recognition due to their inherent...
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Transfer Learning via Representation Learning
The remarkable performance boost of artificial intelligence (AI) algorithms is a result of re-emergence of deep neural networks that have been...
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Discriminative low-rank projection for robust subspace learning
The robustness to outliers, noises, and corruptions has been paid more attention recently to increase the performance in linear feature extraction...
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Seasonal Disorder in Urban Traffic Patterns: A Low Rank Analysis
This article proposes several advances to sparse nonnegative matrix factorization (SNMF) as a way to identify large-scale patterns in urban traffic...
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Substructure Discovery in Commonsense Relations Using Graph Representation Learning
Acquiring commonsense knowledge and reasoning is an important goal in modern natural language processing research. Despite much progress, there is...
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Deep Representation-Based Fuzzy Graph Model for Content-Based Image Retrieval
Image retrieval involves searching for images relevant to a user-provided query image. In this paper, we aim to develop a graph-based model with deep...
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Gait recognition based on multi-feature representation and temporal modeling of periodic parts
Despite the ability of 3D convolutional methods to extract spatio-temporal information simultaneously, they also increase parameter redundancy and...
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Consistent independent low-rank matrix analysis for determined blind source separation
Independent low-rank matrix analysis (ILRMA) is the state-of-the-art algorithm for blind source separation (BSS) in the determined situation (the...
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Knowledge Graph Completion with Triple Structure and Text Representation
Knowledge Graphs (KGs) describe objective facts in the form of RDF triples, each triple contains sufficient semantic information and triple structure...
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A Novel Source Enumeration Method Based on Sparse Representation
A novel source enumeration method based on criterion of searching for the best-matched preset sparse dictionary is presented in this paper, which is...
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A study of sparse representation-based classification for biometric verification based on both handcrafted and deep learning features
Biometric verification is generally considered a one-to-one matching task. In contrast, in this paper, we argue that the one-to-many competitive...
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Concept Representation and Trust Relationship Modeling in Fuzzy Social Networks
Social networks (SNs) are changing all aspects of people’s way of life, especially their decision making and behavioral styles. Trust, as an...
