Results 221 to 230 of about 18,794 (253)

Manifold Warping: Manifold Alignment over Time

Proceedings of the AAAI Conference on Artificial Intelligence, 2021
Knowledge transfer is computationally challenging, due in part to the curse of dimensionality, compounded by source and target domains expressed using different features (e.g., documents written in different languages). Recent work on manifold learning has shown that data collected in real-world settings often have high-dimensional ...
Hoa Trong Vu, Clifton Carey, Sridhar Mahadevan   +2 more
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Aligning Mixed Manifolds

Proceedings of the AAAI Conference on Artificial Intelligence, 2015
Current manifold alignment methods can effectively align data sets that are drawn from a non-intersecting set of manifolds. However, as data sets become increasingly high-dimensional and complex, this assumption may not hold. This paper proposes a novel manifold alignment algorithm, low rank alignment (LRA), that uses a low rank ...
Thomas Boucher, CJ Carey, Sridhar Mahadevan, Melinda Darby Dyar   +3 more
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Multisensor alignment of image manifolds

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013
The access to many sources of satellite information is nowadays a reality. However, few methods allow to consider simultaneously data coming from different sensors, due to the differences in numbers of bands, spatial resolution and changes in the acquisition conditions.
Devis Tuia, Maxime Trolliet, Michele Volpi   +2 more
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Manifold Alignment via Local Tangent Space Alignment

2008 International Conference on Computer Science and Software Engineering, 2008
Manifold alignment (Ham et al., 2005) is about mapping several datasets into a global space, and is of great importance in learning the shared latent structure (Shon et al., 2006), data fusion and multicue data matching (Lafon et al., 2006). In this paper, we propose an algorithm to solve this problem via local tangent space alignment (Zhang et al ...
Gelan Yang, Xue Xu, Jianming Zhang 0003
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Manifold Alignment with Multi-graph Embedding

Proceedings of the ACM Multimedia Asia, 2019
In this paper, a novel manifold alignment approach via multi-graph embedding (MA-MGE) is proposed. Different from the traditional manifold alignment algorithms that use a single graph to describe the latent manifold structure of each dataset, our approach utilizes multiple graphs for modeling multiple local manifolds in multi-view data alignment ...
Changbin Huang, Timothy Apasiba Abeo, Xiangjun Shen   +2 more
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Aligning Coupled Manifolds for Face Hallucination

IEEE Signal Processing Letters, 2009
Many learning-based super-resolution methods are based on the manifold assumption, which claims that point-pairs from the low-resolution representation manifold (LRM) and the corresponding high-resolution representation manifold (HRM) possess similar local geometry.
Bo Li 0086, Hong Chang 0001, Shiguang Shan, Xilin Chen 0001   +3 more
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Manifold alignment using curvature information

2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013), 2013
Manifold learning (ML) is a known non-linear technique for representing high dimensional data. Despite the potential power of ML techniques, they fail in representing an unseen test data accurately. To better model the geometric structure of manifolds, Manifold Alignment (MA) techniques have been proposed recently, where the majority of these ...
Seyed Mohammad Mavadati, Mohammad H. Mahoor, Xiao Zhang 0003   +2 more
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THE HUFFMAN-LIKE ALIGNMENT IN MANIFOLD LEARNING

International Journal of Pattern Recognition and Artificial Intelligence, 2014
In manifold learning, the neighborhood is often called a patch of the manifold, and the corresponding open set is called the local coordinate of the patch. The so-called alignment is to align the local coordinates in the d-dimensional Euclidean space to get the global coordinate of the manifold.
Zhengming Ma, Jing Chen
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Spectral Analysis of Alignment in Manifold Learning

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
Local manifold learning methods produce a collection of overlapping local coordinate systems from a given set of sample points. Alignment is the process to stitch those local systems together to produce a global coordinate system and is done through the computation of the eigensubspace of a so-called alignment matrix.
Hongyuan Zha, Zhenyue Zhang
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Manifold alignment with Schroedinger eigenmaps

SPIE Proceedings, 2016
The sun-target-sensor angle can change during aerial remote sensing. In an attempt to compensate BRDF effects in multi-angular hyperspectral images, the Semi-Supervised Manifold Alignment (SSMA) algorithm pulls data from similar classes together and pushes data from different classes apart.
Juan E. Johnson, Charles M. Bachmann, Nathan D. Cahill   +2 more
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