461 Hits in 4.1 sec

Kernelized Multiview Projection [article]

Mengyang Yu, Li Liu, Ling Shao
2015 arXiv   pre-print
In this paper, we propose a novel unsupervised spectral embedding algorithm called Kernelized Multiview Projection (KMP) to better fuse and embed different feature representations.  ...  Extensive experiments on three popular image datasets demonstrate the effectiveness of our multiview embedding algorithm.  ...  In addition, two non-linear embedding methods, distributed spectral embedding (DSE) and multiview spectral embedding (MSE), are adopted in our comparison, as well.  ... 
arXiv:1508.00430v2 fatcat:3iffyekzlvbbdkoyil5iv77hwe

Table of contents

2014 IEEE Transactions on Image Processing  
Yan 3412 Efficient Semidefinite Spectral Clustering via Lagrange Duality .......................... Y. Yan, C. Shen, and H.  ...  Sun 3698 Stereoscopic and Multiview Processing and Display Bit Allocation Algorithm With Novel View Synthesis Distortion Model for Multiview Video Plus Depth Coding .... ...............................  ... 
doi:10.1109/tip.2014.2338072 fatcat:svx77okuwvc2pnomcmuiha7hmy

Rényi divergence minimization based co-regularized multiview clustering

Shalmali Joshi, Joydeep Ghosh, Mark Reid, Oluwasanmi Koyejo
2016 Machine Learning  
Extensive empirical evaluation suggests improved performance over a variety of existing multiview clustering techniques as well as related methods developed for information fusion with multiview data.  ...  An existing method of probabilistic multiview clustering is recovered as a special case of the proposed method.  ...  -Co-regularized Spectral Clustering (Co-reg (Sp)) (Kumar et al. 2011): This is the state-ofthe-art spectral multiview clustering.  ... 
doi:10.1007/s10994-016-5543-2 fatcat:grnmllf3wrbbfeac3nzl2yny4m

2020 Index IEEE Transactions on Knowledge and Data Engineering Vol. 32

2021 IEEE Transactions on Knowledge and Data Engineering  
Sun, X., +, TKDE Feb. 2020 374-387 Ultra-Scalable Spectral Clustering and Ensemble Clustering.  ...  Li, H., +, TKDE Aug. 2020 1639-1651 Ultra-Scalable Spectral Clustering and Ensemble Clustering.  ... 
doi:10.1109/tkde.2020.3038549 fatcat:75f5fmdrpjcwrasjylewyivtmu

Table of contents

2020 IEEE Geoscience and Remote Sensing Letters  
Xu 2090 Modified Tensor Distance-Based Multiview Spectral Embedding for PolSAR Land Cover Classification .............. .................................................................................  ...  Su 2105 Multitask Deep Learning With Spectral Knowledge for Hyperspectral Image Classification ........ S. Liu and Q.  ... 
doi:10.1109/lgrs.2020.3037586 fatcat:437rgyi2lfbnfa4dkhsyvrrfs4

Apple Variety Recognition Based on Multiview Feature Fusion

Jinjin Cai, Jie Li, Bo Liu, Wei Yao
2020 Revue d'intelligence artificielle : Revue des Sciences et Technologies de l'Information  
The experimental results show that ACRMV with the strategy of multifeature fusion and joint training is superior to its corresponding single-view method and to other multiview methods.  ...  The discriminative image block selection algorithm uses image blocks with greater discrimination as training data to reduce the influence of redundant data.  ...  [15] proposed a multiview clustering method (CRMVSC) based on spectral clustering.  ... 
doi:10.18280/ria.340306 fatcat:czmd636cdzfnhjul3mtjdqfns4

Table of contents

2021 IEEE Geoscience and Remote Sensing Letters  
Vegetation and Land Surface About the cover: Deep Embedded SOM is a kind of deep joint clustering algorithm.  ...  clustering method.  ... 
doi:10.1109/lgrs.2021.3095630 fatcat:gglo2grgyrhctmqdmaejbfq7f4

Spectral clustering with distinction and consensus learning on multiple views data

Peng Zhou, Fan Ye, Liang Du
2018 PLoS ONE  
In this paper, we propose a Distinction based Consensus Spectral Clustering (DCSC), which not only learns a consensus result of clustering, but also explicitly captures the distinct variance of each view  ...  Since multi-view data are available in many real-world clustering problems, multi-view clustering has received considerable attention in recent years.  ...  The essential step of spectral clustering is to learn a spectral embedding.  ... 
doi:10.1371/journal.pone.0208494 pmid:30521611 pmcid:PMC6283548 fatcat:6r752ff45fdwrgq5diz7r56qd4

A Survey on Multi-View Clustering [article]

Guoqing Chao, Shiliang Sun, Jinbo Bi
2018 arXiv   pre-print
We further discuss the relationships between MVC and multi-view representation, ensemble clustering, multi-task clustering, multi-view supervised and semi-supervised learning.  ...  With advances in information acquisition technologies, multi-view data become ubiquitous. Multi-view learning has thus become more and more popular in machine learning and data mining fields.  ...  multiview kernel k-means and multi-view spectral clustering [41] .  ... 
arXiv:1712.06246v2 fatcat:w3b2hfnqyzbbbfcz6t3gl5mlny

Multiview Community Discovery Algorithm via Nonnegative Factorization Matrix in Heterogeneous Networks

Wang Tao, Liu Yang
2017 Mathematical Problems in Engineering  
Taking inspiration from the multiview method, we extend the semisupervised learning from single graph to several bipartite graphs with multiple views.  ...  realize the collaborative learning of different classifiers, thus comprehensively considers the internal structure of all bipartite graphs, and makes all the classifiers tend to reach a consensus on the clustering  ...  With the fast growth of Internet and computational technologies in the past decade, many data mining applications have advanced swiftly from the simple clustering of one data type to the multiple types  ... 
doi:10.1155/2017/8596893 fatcat:tbn2z2z5zrevrboxxoztjg32lu

Multiview Alignment Hashing for Efficient Image Search

Li Liu, Mengyang Yu, Ling Shao
2015 IEEE Transactions on Image Processing  
Hashing is a popular and efficient method for nearest neighbor search in large-scale data spaces, by embedding high-dimensional feature descriptors into a similarity-preserving Hamming space with a low  ...  Since the raised problem is regarded as nonconvex and discrete, our objective function is then optimized via an alternate way with relaxation and converges to a locally optimal solution.  ...  To the best of our knowledge, this is the first time that NMF with multiview hashing has been successfully applied to feature embedding for large-scale similarity search. III.  ... 
doi:10.1109/tip.2015.2390975 pmid:25594968 fatcat:sv2aronnhfdefjjea3ddfqvpi4

Robust Localized Multi-view Subspace Clustering [article]

Yanbo Fan, Jian Liang, Ran He, Bao-Gang Hu, Siwei Lyu
2017 arXiv   pre-print
In multi-view clustering, different views may have different confidence levels when learning a consensus representation.  ...  An efficient iterative algorithm is developed with a convergence guarantee. Experimental results on four benchmarks demonstrate the correctness and effectiveness of the proposed model.  ...  MSC: A weighted multi-view spectral clustering model [Xia et al., 2010] .  ... 
arXiv:1705.07777v1 fatcat:htfkt5gyhzbp5praiut5oth76u

Kernelized Multiview Projection for Robust Action Recognition

Ling Shao, Li Liu, Mengyang Yu
2015 International Journal of Computer Vision  
In this paper, we propose to better fuse and embed different feature representations for action recognition using a novel spectral coding algorithm called Kernelized Multiview Projection (KMP).  ...  Computing the kernel matrices from different features/views via time-sequential distance learning, KMP can encode different features with different weights to achieve a low-dimensional and semantically  ...  To effectively and efficiently learn the complementary nature of different views, multiview spectral embedding (MSE) is introduced in (Xia et al. 2010 ).  ... 
doi:10.1007/s11263-015-0861-6 fatcat:r62ujfqzjrfsfchjcjrd767kwi

Tensor-SVD Based Graph Learning for Multi-View Subspace Clustering

Quanxue Gao, Wei Xia, Zhizhen Wan, Deyan Xie, Pu Zhang
embedded in multi-view data.  ...  We further apply the WTNNM algorithm to multi-view subspace clustering by exploiting the high order correlations embedded in different views.  ...  spectral clustering on the learned graph.  ... 
doi:10.1609/aaai.v34i04.5807 fatcat:e4k6ilzzz5cuvb3rqrwpaytada

2019 Index IEEE Transactions on Knowledge and Data Engineering Vol. 31

2020 IEEE Transactions on Knowledge and Data Engineering  
., +, TKDE Aug. 2019 1624-1629 Fast Failure Recovery in Vertex-Centric Distributed Graph Processing Sys- tems. Lu, W., +, TKDE April 2019 733-746 Graph Structure Fusion for Multiview Clustering.  ...  Zhang, Z., +, TKDE Sept. 2019 1750-1764 One-Step Multi-View Spectral Clustering.  ... 
doi:10.1109/tkde.2019.2953412 fatcat:jkmpnsjcf5a3bhhf4ian66mj5y
« Previous Showing results 1 — 15 out of 461 results