A multi-view time series model for share turnover prediction
Share turnover is a key indicator for investing in the stock market, which represents how easy or difficult it is to trade a stock. Several techniques have been proposed to predict share turnover values. However, they are often inaccurate because ...
Incomplete multi-view clustering with incomplete graph-regularized orthogonal non-negative matrix factorization
Incomplete multi-view clustering (IMC) has achieved widespread attention due to its advantage in fusing the multi-view information when the view samples are unobserved partly. Recently, it is shown that the clustering performance in the subspace ...
Sign language recognition and translation network based on multi-view data
Sign language recognition and translation can address the communication problem between hearing-impaired and general population, and can break the sign language boundariesy between different countries and different languages. Traditional sign ...
A multi-view multi-omics model for cancer drug response prediction
Cancer drug response prediction is the fundamental task in precision medicine, which provides opportunities for cancer therapy. Several methods have been proposed to screen drugs, via building computational models on multi-omics data. However, the ...
Nonconvex low-rank and sparse tensor representation for multi-view subspace clustering
Multi-view subspace clustering has attracted significant attention due to the popularity of multi-view datasets. The effectiveness of the existing multi-view clustering methods highly depends on the quality of the affinity matrix. To derive a high ...
Face aging with pixel-level alignment GAN
Face aging is of great significance in cross-time identity verification problem. However, there is still a huge gap between the synthesized face image and the real face in terms of quality and consistency due to identity ambiguity and image ...
Trace ratio criterion for multi-view discriminant analysis
Learning from heterogeneous views, termed multi-view learning (MvL), is a significant yet challenging problem in computer vision. Many existing MvL methods apply the two-view principle to multi-view scenarios, but this pairwise approach is neither ...
Edge-enhanced dual discriminator generative adversarial network for fast MRI with parallel imaging using multi-view information
- Jiahao Huang,
- Weiping Ding,
- Jun Lv,
- Jingwen Yang,
- Hao Dong,
- Javier Del Ser,
- Jun Xia,
- Tiaojuan Ren,
- Stephen T. Wong,
- Guang Yang
In clinical medicine, magnetic resonance imaging (MRI) is one of the most important tools for diagnosis, triage, prognosis, and treatment planning. However, MRI suffers from an inherent slow data acquisition process because data is collected ...
M-FFN: multi-scale feature fusion network for image captioning
In this work, we present a novel multi-scale feature fusion network (M-FFN) for image captioning task to incorporate discriminative features and scene contextual information of an image. We construct multi-scale feature fusion network by ...
Locality sensitive hashing with bit selection
Locality sensitive hashing (LSH), one of the most popular hashing techniques, has attracted considerable attention for nearest neighbor search in the field of image retrieval. It can achieve promising performance only if the number of the ...
IBMvSVM: An instance-based multi-view SVM algorithm for classification
As an emerging research direction of machine learning, the multi-view learning (MVL) pays attention to the tasks that learn from datasets with several distinct views to achieve better generalization performance. Recently, various Support Vector ...
Co-clustering based classification of multi-view data
Multi-view learning is an attractive area of research where data is represented using multiple views, each containing some useful information. Many multi-view learning algorithms use a unified objective function that needs to be optimized ...
A multi-mode traffic flow prediction method with clustering based attention convolution LSTM
Increasing traffic congestion is a major obstacle to the development of cities. The prediction of traffic flow is very important to city planning and dredging. A good model of flow is able to accurately predict future flow by learning historical ...
Multi-view attention-convolution pooling network for 3D point cloud classification
Classifying 3D point clouds is an important and challenging task in computer vision. Currently, classification methods using multiple views lose characteristic or detail information during the representation or processing of views. For this reason,...
Cross-view vehicle re-identification based on graph matching
Cross-view identification is one of the challenges in the task of vehicle re-identification. Because of the different shapes, structures, and surface area, changes in viewing angle have a greater impact on vehicle re-ID than on person re-ID. ...
Incomplete multi-view clustering with multiple imputation and ensemble clustering
Multi-view clustering is an important and challenging task in machine learning and data mining. In the past decade, this topic attracted much attention and there have been many progress achieved in this field. However, in reality, due to different ...
Incomplete multi-view clustering based on weighted sparse and low rank representation
Multi-view clustering utilizes the consistency and complementarity between views to group entities well. However, in real life, the lack of instances in some views often occurs, which not only reduces the available information, but also increases ...
Speech synthesis with face embeddings
Human beings are capable of imagining a person’s voice according to his or her appearance because different people have different voice characteristics. Although researchers have made great progress in single-view speech synthesis, there are few ...
Semi-supervised multi-view binary learning for large-scale image clustering
Large-scale image clustering has attracted sustained attention in machine learning. The traditional methods based on real value representation often suffer from the data storage and calculation. To deal with these problems, the methods based on ...
Robust deep multi-view subspace clustering networks with a correntropy-induced metric
Since multi-view subspace clustering combines the advantages of deep learning to capture the nonlinear nature of data, deep multi-view subspace clustering methods have demonstrated superior ability to shallow multi-view subspace clustering ...
Deep mutual information multi-view representation for visual recognition
Multi-view representation is a crucial but challenging issue in visual recognition task. To address this issue, a deep mutual information multi-view representation method is proposed in this paper. Firstly, multi-view inputs are fed to the encoder ...
Online unsupervised cross-view discrete hashing for large-scale retrieval
Cross-view hashing has shown great potential for large-scale retrieval due to its superiority in terms of computation and storage. In real-world applications, data emerges in a streaming manner, e.g., new images and tags are uploaded to social ...
Efficient multi-view clustering networks
In the last decade, deep learning has made remarkable progress on multi-view clustering (MvC), with existing literature adopting a broad target to guide the network learning process, such as minimizing the reconstruction loss. However, despite ...
Frobenius norm-regularized robust graph learning for multi-view subspace clustering
Graph learning methods have been widely used for multi-view clustering. However, such methods have the following challenges: (1) they usually perform simple fusion of fixed similarity graph matrices, ignoring its essential structure. (2) they are ...
Multi-view k-proximal plane clustering
Multi-view clustering is an active direction in machine learning and pattern recognition which aims at exploring the consensus and complementary information among multiple views. In the last few years, a number of methods based on multi-view ...
A modified ELECTRE II method with double attitude parameters based on linguistic Z-number and its application for third-party reverse logistics provider selection
As more attention is given to environmental protection, sustainable development has become a hot topic for the international community and the companies are motivated to focus on reverse logistics (RL) in their operations for resource conservation ...
An optimal and secure resource searching algorithm for unstructured mobile peer-to-peer network using particle swarm optimization
The outrageous demand for file sharing among peers has become a significant development of the Peer-to-Peer (P2P) communication system during the past few years. The essence of recent P2P file-sharing systems has been driven mainly by their ...
Sentiment aware tensor model for multi-criteria recommendation
With the advance of sentiment analysis techniques, several studies have been on Multi-Criteria Recommender Systems (MCRS) leveraging sentiment information. However, partial preferences quite and naturally happen in MCRS and negatively affect the ...
STGMN: A gated multi-graph convolutional network framework for traffic flow prediction
Accurate traffic flow prediction is crucial for the development of intelligent transportation. It can not only effectively avoid traffic congestion and other traffic problems, but also provide a data basis for other complex tasks. The rapid ...
