Results 271 to 280 of about 3,233,192 (305)

Robust multi-view data clustering with multi-view capped-norm K-means

Neurocomputing, 2018
Abstract Real-world data sets are often comprised of multiple representations or views which provide different and complementary aspects of information. Multi-view clustering is an important approach to analyze multi-view data in a unsupervised way.
Shudong Huang, Yazhou Ren 0001, Zenglin Xu   +2 more
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Linear Multi View Reconstruction with Missing Data

2002
General multi view reconstruction from affine or projective cameras has so far been solved most efficiently using methods of factorizing image data matrices into camera and scene parameters. This can be done directly for affine cameras [18] and after computing epipolar geometry for projective cameras [17].
Carsten Rother, Stefan Carlsson
openaire   +1 more source

Multi-view Similarity Learning of Manifold Data

2019
In recent years, multi-view learning methods have developed rapidly where graph-based approaches have achieved good performance. Usually, these learning methods construct information graph for each view or fuse different views into one graph. In this paper, a novel multi-view learning model that learns one similarity matrix for all views named Multi ...
Rui-Rui Wang, Sibao Chen 0001, Bin Luo 0001, Jian Zhang 0061   +3 more
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Modeling and Maintaining Multi-view Data Warehouses

1999
Data warehouses are designed mostly as centralized systems, andt he majority of update maintenance algorithms are tailored for this specific model. Maintenance methods have been proposed either under the assumption of a single view data warehouse, a multi-view centralized model, or a multi-view distributed system with strict synchronization ...
Ioana Stanoi, Divyakant Agrawal, Amr El Abbadi   +2 more
openaire   +1 more source

Multi-View Data Completion

2018
Multi-view learning has been explored in various applications such as bioinformatics, natural language processing and multimedia analysis. Often multi-view learning methods commonly assume that full feature matrices or kernel matrices for all views are available. However, in partial data analytics, it is common that information from some sources is not
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Multi-view Clustering of Social-based Data

2020
Real-world, social phenomena produce various types of data, like explicit networks or user-emitted text. When different sets of data describe the same entities, thedata is termed multi-view or multi-modal. A distinct advantage of multi-view data is that different views may better capture different aspects of the latent structure ofthe data.
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Multi-View Visual Recognition of Imperfect Testing Data

Proceedings of the 23rd ACM international conference on Multimedia, 2015
A practical yet under-explored problem often encountered by multimedia researchers is the recognition of imperfect testing data, where multiple sensing channels are deployed but interference or transmission distortion corrupts some of them. Typical cases of imperfect testing data include missing features and feature misalignments.
Qilin Zhang 0004, Gang Hua 0001
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On efficient use of multi-view data for activity recognition

Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras, 2010
The focus of the paper is on studying ??ve di??erent meth- ods to combine multi-view data from an uncalibrated smart camera network for human activity recognition. The multi- view classi??cation scenarios studied can be divided to two categories: view selection and view fusion methods.
Tommi Määttä, Aki Härmä, Hamid K. Aghajan   +2 more
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Knowledge-Driven Interpretation of Multi-View Data in Medicine

2018
We propose a new approach to clinical decision support with interpretable recommendations from multi-view data. We introduce a Bayesian network structure learning method to help identify the relevant factors and their relationships. Guided by minimal domain knowledge, this method highlights the significant associations among the demography, medical and
Parvathy Sudhir Pillai, Lei Feng, Tze-Yun Leong   +2 more
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Multi-View Federated Learning with Data Collaboration

2022 14th International Conference on Machine Learning and Computing (ICMLC), 2022
Yitao Yang, Xiucai Ye, Tetsuya Sakurai
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