Results 261 to 270 of about 5,224,308 (308)

Unified subspace learning for incomplete and unlabeled multi-view data

Pattern Recognition, 2017
Qiyue Yin, Shu Wu, Liang Wang
semanticscholar   +3 more sources

An active three-way clustering method via low-rank matrices for multi-view data

Information Sciences, 2020
In recent years, multi-view clustering algorithms have shown promising performance by combining multiple sources or views of datasets. A problem that has not been addressed satisfactorily is the uncertain relationship between an object and a cluster ...
Hong Yu, Xincheng Wang, Guoyin Wang, Xianhua Zeng   +3 more
semanticscholar   +1 more source

Shared Multi-View Data Representation for Multi-Domain Event Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Internet platforms provide new ways for people to share experiences, generating massive amounts of data related to various real-world concepts. In this paper, we present an event detection framework to discover real-world events from multiple data ...
Zhenguo Yang, Qing Li, Wenyin Liu, Jianming Lv   +3 more
semanticscholar   +1 more source

Co-Learning Non-Negative Correlated and Uncorrelated Features for Multi-View Data

IEEE Transactions on Neural Networks and Learning Systems, 2020
Multi-view data can represent objects from different perspectives and thus provide complementary information for data analysis. A topic of great importance in multi-view learning is to locate a low-dimensional latent subspace, where common semantic ...
Liang Zhao, Tao Yang, Jie Zhang, Zhikui Chen, Yi Yang, Z. J. Wang   +5 more
semanticscholar   +1 more source

Tensor-Based Multi-View Block-Diagonal Structure Diffusion for Clustering Incomplete Multi-View Data

2021 IEEE International Conference on Multimedia and Expo (ICME), 2021
In this paper, we propose a novel incomplete multi-view clustering method, in which a tensor nuclear norm regularizer elegantly diffuses the information of multi-view block-diagonal structure across different views. By exploring the membership between observed and missing samples and that between missing ones in each incomplete view with the guidance ...
Zhenglai Li, Chang Tang, Xinwang Liu, Xiao Zheng, Wei Zhang, En Zhu   +5 more
openaire   +1 more source

Multi-view kernel-based data analysis

2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE), 2016
The input data features set for many data driven tasks is high-dimensional while the intrinsic dimension of the data is low. Data analysis methods aim to uncover the underlying low dimensional structure imposed by the low dimensional hidden parameters by utilizing distance metrics that considers the set of attributes as a single monolithic set. However,
Amir Averbuch, Moshe Salhov, Ofir Lindenbaum, Avi Silberschatz, Yoel Shkolnisky   +4 more
openaire   +1 more source

Multi-view Clustering on Relational Data

2014
Clustering is a popular task in knowledge discovery. In this chapter we illustrate this fact with a new clustering algorithm that is able to partition objects taking into account simultaneously their relational descriptions given by multiple dissimilarity matrices.
Despeyroux, Thierry, de Carvahlo, Francisco de A.T., Lechevallier, Yves, de Melo, Filipe   +3 more
openaire   +1 more source

Multi-view 3D scanned data registration

Proceedings of the 2008 C3S2E conference on - C3S2E '08, 2008
We propose a new algorithm for registering 3D scans obtained from different views of an object. Our work differs from the popular ICP based approach since we minimize error in signed distance function instead of squared distance between sampled surface points themselves.
Sushil Bhakar, Ran Wang, Sudhir Mudur
openaire   +1 more source

Portrait4D-v2: Pseudo Multi-View Data Creates Better 4D Head Synthesizer

European Conference on Computer Vision
In this paper, we propose a novel learning approach for feed-forward one-shot 4D head avatar synthesis. Different from existing methods that often learn from reconstructing monocular videos guided by 3DMM, we employ pseudo multi-view videos to learn a 4D
Yu Deng, Duomin Wang, Baoyuan Wang
semanticscholar   +1 more source

A survey on representation learning for multi-view data

Neural Networks
Multi-view clustering has become a rapidly growing field in machine learning and data mining areas by combining useful information from different views for last decades.
Yalan Qin, Xinpeng Zhang, Shui Yu, Guorui Feng   +3 more
semanticscholar   +1 more source