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Discriminative Locality Alignment
[chapter]
2008
Lecture Notes in Computer Science
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In this paper, we propose a new algorithm, termed Discriminative Locality Alignment (DLA), to deal with these problems. ...
, in sample weighting, each part optimization is weighted by the margin degree, a measure of the importance of a given sample; and finally, in whole alignment, the alignment trick is used to align all ...
Conclusions In this paper, we have proposed a new linear dimensionality reduction algorithm, termed Discriminative Locality Alignment (DLA). ...
doi:10.1007/978-3-540-88682-2_55
fatcat:llxu3xcgafal5a7pzx3dm56gcq
Local Discriminant Hyperalignment for multi-subject fMRI data alignment
[article]
2016
arXiv
pre-print
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By incorporating the idea of Local Discriminant Analysis (LDA) into CCA, this paper proposes Local Discriminant Hyperalignment (LDHA) as a novel supervised HA method, which can provide better functional ...
alignment for MVP analysis. ...
As the main contribution of this paper, we introduce Local Discriminant Hyperalignment (LDHA) method, which incorporates the idea of Local Discriminate Analysis (LDA) into CCA (Peng, Zhang, and Zhang ...
arXiv:1611.08366v1
fatcat:44tvjzlhnnaglnlnhmatxbmfim
Local Discriminant Hyperalignment for multi-subject fMRI data alignment
[article]
2016
bioRxiv
pre-print
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By incorporating the idea of Local Discriminant Analysis (LDA) into CCA, this paper proposes Local Discriminant Hyperalignment (LDHA) as a novel supervised HA method, which can provide better functional ...
alignment for MVP analysis. ...
As the main contribution of this paper, we introduce Local Discriminant Hyperalignment (LDHA) method, which incorporates the idea of Local Discriminate Analysis (LDA) into CCA (Peng, Zhang, and Zhang ...
doi:10.1101/092247
fatcat:iw3mfk2osbchdnjzqlsapnaqom
Enhanced discriminative locality alignment and its kernel extension
2011
Optical Engineering: The Journal of SPIE
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Subject terms: discriminative locality alignment; part optimization; whole alignment; enhanced discriminative locality alignment; kernel enhanced discriminative locality alignment. Paper 110173R ...
Although discriminative locality alignment (DLA), which is based on the idea of part optimization and whole alignment, has better performance than classical methods in feature extraction, DLA is too overly ...
Therefore, kernel-enhanced discriminative locality alignment (KEDLA) is further proposed in this paper. ...
doi:10.1117/1.3605477
fatcat:gnwu6mbo3zcgppaw5e5nzelfim
Prostate lesion detection and localization based on locality alignment discriminant analysis
2017
Medical Imaging 2017: Computer-Aided Diagnosis
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Here, we developed an algorithm based on locality alignment discriminant analysis (LADA) technique, which can be considered as a version of linear discriminant analysis (LDA) localized to patches in the ...
However, in previous investigations, lesion localization was achieved mainly by manual segmentation, which is time-consuming and prone to observer variability. ...
Locality Alignment Discriminant analysis (LADA) A disadvantage of LDA is that S w and S b were built globally based on the entire training set. ...
doi:10.1117/12.2255621
dblp:conf/micad/LinCZGBCKCWC17
fatcat:6hvbtaa77bhlzlvpog4wdo6tba
Plant Leaf Recognition through Local Discriminative Tangent Space Alignment
2016
Journal of Electrical and Computer Engineering
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The proposed method can embrace part optimization and whole alignment and encapsulate the geometric and discriminative information into a local patch. ...
In this paper, a dimensionality reduction method based on local discriminative tangent space alignment (LDTSA) is introduced for plant leaf recognition based on leaf images. ...
locally linear embedding (HLLE) in [10] , maximum variance unfolding (MVU) in [11] , local tangent space alignment (LTSA) in [12] , local spline embedding (LSE) in [13] , and local discriminative ...
doi:10.1155/2016/1989485
fatcat:4mekshzznjeg5g63rnumlaqsqm
Semisupervised Discriminative Locally Enhanced Alignment for Hyperspectral Image Classification
2013
IEEE Transactions on Geoscience and Remote Sensing
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This paper proposes a new semisupervised dimension reduction (DR) algorithm based on a discriminative locally enhanced alignment technique. ...
Discriminative locality alignment (DLA) [12] , which is based on the patch alignment strategy [13] , selects neighbors for a local patch from both intraclass and interclass to enlarge the margin between ...
Based on the aforementioned consideration, this paper proposes a DR method based upon a patch alignment framework for hyperspectral imagery, named semisupervised discriminative locally enhanced alignment ...
doi:10.1109/tgrs.2012.2230445
fatcat:w437tg7jhngp7fm2pzup7bl6ue
Local Discriminant Hyperalignment for Multi-Subject fMRI Data Alignment
2017
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
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By incorporating the idea of Local Discriminant Analysis (LDA) into CCA, this paper proposes Local Discriminant Hyperalignment (LDHA) as a novel supervised HA method, which can provide better functional ...
alignment for MVP analysis. ...
As the main contribution of this paper, we introduce Local Discriminant Hyperalignment (LDHA) method, which incorporates the idea of Local Discriminate Analysis (LDA) into CCA (Peng, Zhang, and Zhang ...
doi:10.1609/aaai.v31i1.10506
fatcat:r6yf33uaz5bflf3np6etzudnzi
Tensor Discriminative Locality Alignment for Hyperspectral Image Spectral–Spatial Feature Extraction
2013
IEEE Transactions on Geoscience and Remote Sensing
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In particular, we define a tensor organization scheme for representing a pixel's spectral-spatial feature and develop tensor discriminative locality alignment (TDLA) for removing redundant information ...
manifold-learning algorithm, under the umbrella of multilinear algebra, i.e., tensor discriminative locality alignment (TDLA) for hyperspectral remote sensing image spectral-spatial feature representation ...
Then, the TDLA algorithm is used to preserve the discriminability of the classes for classification by considering the discriminative locality information in the optimization. ...
doi:10.1109/tgrs.2012.2197860
fatcat:qj3hgn5sfbhg3jzhekzmgfnf4m
Bio-Inspired Structure Representation Based Cross-View Discriminative Subspace Learning via Simultaneous Local and Global Alignment
2020
Complexity
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Secondly, a local alignment is constructed with two designed graphs to guide the subspace decomposition in a pairwise way. ...
Finally, the global discriminative constraint on distribution center in each view is designed for further alignment improvement. ...
Graph-Based Discriminative Local Alignment. ...
doi:10.1155/2020/8872348
fatcat:xuxypc3pxfaupkfghegoscmkne
Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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It is known that after a perfect domain alignment the domain-invariant representations of two domains should share the same characteristics from perspective of the overview and also any local piece. ...
Specifically, the hierarchical domain alignments including class-wise alignment, groupwise alignment and global alignment are first constructed. ...
D cls denotes adversarial discriminators for locally class-wise distribution alignment. ...
doi:10.1109/cvpr42600.2020.00410
dblp:conf/cvpr/HuKSC20
fatcat:qpa65m2wova3jenahvku2t2c7a
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation
[article]
2022
arXiv
pre-print
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Then, a local feature mask is integrated to reduce the 'inter-gap' for local features by prioritizing those discriminative features with larger domain gap. ...
This combination of global and local alignment can precisely localize the crucial regions in segmentation target while preserving the overall semantic consistency. ...
Local Alignment: Segmentation Subnet with Dual Discriminators. As shown in Fig. 3 , local alignment stage is mainly composed of a segmentation network S and two discriminator networks D 1 , D 2 . ...
arXiv:2205.11888v1
fatcat:a5z263udqbantdapyqnqmjvhse
Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation
[article]
2020
arXiv
pre-print
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An adaptive entropy max-min adversarial learning scheme is designed to optimally align these hundreds of local contextual-relations across domain without requiring discriminator or extra computation overhead ...
The idea is to take a closer look at region-wise feature representations and align them for local-level consistencies. ...
However, the discriminator might deconstruct this existing local alignment during implementing the global marginal distribution alignment. ...
arXiv:2007.02424v2
fatcat:kby6leqi2zdkrniapzwrtnlxny
SALIENCE: An Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity Recognition
[article]
2021
arXiv
pre-print
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It aligns the data of each sensor separately to achieve local alignment, while uniformly aligning the data of all sensors to ensure global alignment. ...
In addition, an attention mechanism is proposed to focus the activity classifier of SALIENCE on the sensors with strong feature discrimination and well distribution alignment. ...
SALIENCE combines local and global discriminators to align the feature distributions. Local discriminators are independent of each other, which provide sensor-level local alignment. ...
arXiv:2108.10213v1
fatcat:yzhdiqdp25crzl3rufuaykjxxm
Exploiting Local Feature Patterns for Unsupervised Domain Adaptation
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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In this paper, we present a method for learning domain-invariant local feature patterns and jointly aligning holistic and local feature statistics. ...
We show that the learned local feature patterns are more generic and transferable and a further local feature distribution matching enables fine-grained feature alignment. ...
Local Feature Patterns Learning In this section, we learn a cluster of discriminative local feature patterns to enable joint holistic and local feature alignment. ...
doi:10.1609/aaai.v33i01.33015401
fatcat:4vfeboxgtjhldilik3lyuvmwfa
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