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Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity [article]

Dong Huang, Chang-Dong Wang, Jian-Huang Lai
2022 arXiv   pre-print
Then, a set of diversified base clusterings for different view groups are obtained via fast graph partitioning, which are further formulated into a unified bipartite graph for final clustering in the late-stage  ...  Remarkably, FastMICE has almost linear time and space complexity, and is free of dataset-specific tuning.  ...  ACKNOWLEDGMENTS This project was supported by the NSFC (61976097, 61876193 & 62076258) and the Natural Science Foundation of Guangdong Province (2021A1515012203).  ... 
arXiv:2203.11572v1 fatcat:cckfvgu3tbbenap6ebjwsj3coq

Efficient One-Pass Multi-View Subspace Clustering with Consensus Anchors

Suyuan Liu, Siwei Wang, Pei Zhang, Kai Xu, Xinwang Liu, Changwang Zhang, Feng Gao
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
To address these issues, we propose a scalable and parameter-free MVSC method to directly output the clustering labels with optimal anchor graph, termed as Efficient One-pass Multi-view Subspace Clustering  ...  Specially, we combine anchor learning and graph construction into a uniform framework to boost clustering performance.  ...  and 62006237).  ... 
doi:10.1609/aaai.v36i7.20723 fatcat:6ocjoh365zaztnwhfljcmlkswq

Tensor-based Multi-view Spectral Clustering via Shared Latent Space [article]

Qinghua Tao, Francesco Tonin, Panagiotis Patrinos, Johan A.K. Suykens
2022 arXiv   pre-print
Numerical experiments verify that our method is effective regarding accuracy, efficiency, and interpretability, showing a sharp eigenvalue decay and distinct latent variable distributions.  ...  In this paper, a new method for MvSC is proposed via a shared latent space from the Restricted Kernel Machine framework.  ...  AI -Integrating Reasoning, Learning and Optimization), and Leuven.AI Institute.  ... 
arXiv:2207.11559v1 fatcat:7rqz6fn35ngl3mgxlvjvzkrkp4

A multiobjective multi-view cluster ensemble technique: Application in patient subclassification

Sayantan Mitra, Sriparna Saha, Yang Li
2019 PLoS ONE  
Initially, a large number of diverse clustering solutions (called base partitionings) are generated for each omic dataset using four clustering algorithms, viz., k means, complete linkage, spectral and  ...  An elaborated comparative study with several baseline methods and five state-of-the-art models is performed to show the effectiveness of the algorithm.  ...  In [29] , authors proposed an parameter-free clustering models, Adaptively Weighted Procrustes technique, for multiview clustering.  ... 
doi:10.1371/journal.pone.0216904 pmid:31120942 pmcid:PMC6533037 fatcat:bwvm4nl7ybem7i3ylxfjb7hp3q

2020 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 31

2020 IEEE Transactions on Neural Networks and Learning Systems  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  Shen, Q., +, TNNLS March 2020 1010-1021 Person Reidentification via Multi-Feature Fusion With Adaptive Graph Learning. Zhou, R., +, TNNLS May 2020 1592-1601 Robust Structured Graph Clustering.  ... 
doi:10.1109/tnnls.2020.3045307 fatcat:34qoykdtarewhdscxqj5jvovqy

The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools [article]

David Camacho, Àngel Panizo-LLedot, Gema Bello-Orgaz, Antonio Gonzalez-Pardo, Erik Cambria
2020 arXiv   pre-print
This work proposes the definition of four different dimensions, namely Pattern & Knowledge discovery, Information Fusion & Integration, Scalability, and Visualization, which are used to define a set of  ...  essential features (or dimensions) in SNA; (3) finally, we provide a quantitative analysis of a set of popular SNA tools and frameworks.  ...  This collaboration will promote the use of SNA technologies and fostering new developments, but it will not be possible without the cooperation of the community, so your contribution will be highly appreciated  ... 
arXiv:2002.09485v1 fatcat:4b6fgh3lkvgn7cfx7mrwtyq24a

2021 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 32

2021 IEEE Transactions on Neural Networks and Learning Systems  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  Yazidi, A., +, TNNLS Aug. 2021 3444-3457 An Efficient Parameter-Free Learning Automaton Scheme.  ... 
doi:10.1109/tnnls.2021.3134132 fatcat:2e7comcq2fhrziselptjubwjme

2019 Index IEEE Transactions on Signal Processing Vol. 67

2019 IEEE Transactions on Signal Processing  
., +, TSP Dec. 15, 2019 6411-6423 Eigendecomposition-Free Sampling Set Selection for Graph Signals. Saki- yama, A., +, TSP May 15, 2019 2679-2692 Graph Multiview Canonical Correlation Analysis.  ...  ., +, TSP July 1, 2019 3361-3371 Fast Graph Fourier Transforms Based on Graph Symmetry and Bipartition.  ...  M Machine bearings Quickest Change Detection in the Presence of a Nuisance Change. Lau, T.S., +, TSP Oct. 15  ... 
doi:10.1109/tsp.2020.2968163 fatcat:dvvpqntb2rc2bjed5nnk4xora4

Statistical Latent Space Approach for Mixed Data Modelling and Applications [article]

Tu Dinh Nguyen, Truyen Tran, Dinh Phung, Svetha Venkatesh
2017 arXiv   pre-print
To tackle these challenges, we introduce parameter sharing and balancing extensions to our recent model, the mixed-variate restricted Boltzmann machine (MV.RBM) which can transform heterogeneous data into  ...  The experimental results demonstrate the models perform better than baseline methods in medical data and outperform state-of-the-art rivals in image dataset.  ...  This setting gives a reasonable clustering. The other two clustering methods require a prior number of clusters, and here we use the output from the AP.  ... 
arXiv:1708.05594v1 fatcat:5wgecztyvnhu3lua6hawt5mday

A Survey of Visual Transformers [article]

Yang Liu, Yao Zhang, Yixin Wang, Feng Hou, Jin Yuan, Jiang Tian, Yang Zhang, Zhongchao Shi, Jianping Fan, Zhiqiang He
2022 arXiv   pre-print
to organize the representative methods according to their motivations, structures, and application scenarios.  ...  In this survey, we have reviewed over one hundred of different visual Transformers comprehensively according to three fundamental CV tasks and different data stream types, where a taxonomy is proposed  ...  These multiview features are then fed into a stack of the Transformer decoders for text data fusion.  ... 
arXiv:2111.06091v3 fatcat:a3fq6lvvzzgglb3qtus5qwrwpe

Big networks: A survey

Hayat Dino Bedru, Shuo Yu, Xinru Xiao, Da Zhang, Liangtian Wan, He Guo, Feng Xia
2020 Computer Science Review  
Big network models and related approaches, including ranking methods, partition approaches, as well as network embedding algorithms are systematically introduced.  ...  A network is a typical expressive form of representing complex systems in terms of vertices and links, in which the pattern of interactions amongst components of the network is intricate.  ...  "Let G = (U, V, E) be a bipartite graph, B ∈ U and x ∈ V be two vertices in G, and (B, x) ∈ E. Denote the U-projected graph of G as G u = (U, E u ).  ... 
doi:10.1016/j.cosrev.2020.100247 fatcat:pmuxvvbprnc4jcy3gqmrjyf4tq

Broad Learning for Healthcare [article]

Bokai Cao
2018 arXiv   pre-print
analyzed by research institutes), graph data (e.g., brain connectivity networks), and sequence data (e.g., digital footprints recorded on smart sensors).  ...  and machine learning tasks.  ...  Ranu and Singh proposed a scalable approach, called GraphSig, that is capable of mining discriminative subgraphs with a low frequency threshold (120).  ... 
arXiv:1803.08978v1 fatcat:m744ijnjpzetpg6g5a4h3z26ye

Tensors for Data Mining and Data Fusion

Evangelos E. Papalexakis, Christos Faloutsos, Nicholas D. Sidiropoulos
2016 ACM Transactions on Intelligent Systems and Technology  
Tensors and tensor decompositions are very powerful and versatile tools that can model a wide variety of heterogeneous, multiaspect data.  ...  Finally, we conclude with a list of challenges and open problems that outline exciting future research directions.  ...  IIS-1247489 and IIS-1247632.  ... 
doi:10.1145/2915921 fatcat:annpad5w2jcvnb4d3e5imiemlu

Video Skimming

Vivekraj V. K., Debashis Sen, Balasubramanian Raman
2019 ACM Computing Surveys  
We present a taxonomy of video skimming approaches, and discuss their evolution highlighting key advances.  ...  Video skimming, also known as dynamic video summarization, generates a temporally abridged version of a given video.  ...  The authors would also like to thank the associate editors and editor in chief for identifying the potential in this survey and taking it through the review process.  ... 
doi:10.1145/3347712 fatcat:h4zbzmdfx5c2rm3dm4cmmzrsoa

Table of contents

2019 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)  
Jan van Gemert (Delft University of Technology, The Netherlands) Contact-Free Monitoring of Physiological Parameters in People With Profound Intellectual and Multiple Disabilities 1664 Gašper Slapnicar  ...  Scalable Scene Graph Generation 1754 Nikolaos Gkanatsios (Deeplab, Greece), Vassilis Pitsikalis (Deeplab, Greece), Petros Koutras (National Technical University of Athens, Greece), and Petros Maragos  ... 
doi:10.1109/iccvw.2019.00004 fatcat:balgnbs6n5gbvosrkz3mx5gn6m
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