Results 41 to 50 of about 822,037 (305)
Metric Learning via Cross-Validation
Statistica Sinica, 2022 Summary: In this paper, we propose a \textit{cross-validation metric learning} approach to learn a distance metric for dimension reduction in the multiple-index model. We minimize a leave-one-out cross-validation-type loss function, where the unknown link function is approximated by a metric-based kernel-smoothing function. To the best of our knowledge,
Dai, Linlin +3 more
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Metric-learning-assisted domain adaptation [PDF]
Neurocomputing, 2021 Domain alignment (DA) has been widely used in unsupervised domain adaptation. Many existing DA methods assume that a low source risk, together with the alignment of distributions of source and target, means a low target risk. In this paper, we show that this does not always hold.
Yin, Yueming +3 more
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Adversarial Similarity Metric Learning for Kinship Verification
IEEE Access, 2019 Given a pair of facial images, it is an interesting yet challenging problem to determine if there is a kin relation between them. Recent research on that topic has made encouraging progress by learning a kin similarity metric from kinship data.
Zeqiang Wei +4 more
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Metric Learning Based Convolutional Neural Network for Left-Right Brain Dominance Classification
IEEE Access, 2021 The educational concepts upholding the theory of brain dominance have been developed for more than 30 years. Some academicians developed a series of the syllabus to exploit the brain capability of students by training their weaker hemisphere of the brain.
Zheng You Lim +2 more
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, 2020 Code and documentation is available at https://www.github.com/KevinMusgrave/pytorch-metric ...
Musgrave, Kevin +2 more
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K-L Divergence Based Image Classification and the Application [PDF]
Journal of Systemics, Cybernetics and Informatics, 2021 Image classification is widely used in many fields. Traditional metric learning based classification methods always maximize between-class distances and minimize within-class distances based on features calculated from each individual.
Fuhua Chen, Xuemao Zhang, Guangtai Ding
doaj
Deep Hash Remote-Sensing Image Retrieval Assisted by Semantic Cues
Remote Sensing, 2022 With the significant and rapid growth in the number of remote-sensing images, deep hash methods have become a research topic. The main work of deep hash method is to build a discriminate embedding space through the similarity relation between sample ...
Pingping Liu +3 more
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Learning to Rank Using Localized Geometric Mean Metrics
, 2017 Many learning-to-rank (LtR) algorithms focus on query-independent model, in which query and document do not lie in the same feature space, and the rankers rely on the feature ensemble about query-document pair instead of the similarity between query ...
King, Irwin, Lyu, Michael, Su, Yuxin
core +1 more source
Learning to Approximate a Bregman Divergence [PDF]
, 2020 Bregman divergences generalize measures such as the squared Euclidean distance and the KL divergence, and arise throughout many areas of machine learning.
Castanon, David +4 more
core
Metric Learning for Image Registration [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Image registration is a key technique in medical image analysis to estimate deformations between image pairs. A good deformation model is important for high-quality estimates. However, most existing approaches use ad-hoc deformation models chosen for mathematical convenience rather than to capture observed data variation.
Niethammer, Marc +2 more
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