Results 21 to 30 of about 210,501 (299)
Metric Learning for Structured Data
, 2019 Distance measures form a backbone of machine learning and information retrieval in many application fields such as computer vision, natural language processing, and biology. However, general-purpose distances may fail to capture semantic particularities of a domain, leading to wrong inferences downstream. Motivated by such failures, the field of metric
Paaßen, Benjamin ; https://orcid.org/
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Fault Diagnosis of Rolling Bearing Based on Modified Deep Metric Learning Method
Shock and Vibration, 2021 A novel fault diagnosis method of rolling bearing based on deep metric learning and Yu norm is proposed in this paper, which is called a deep metric learning method based on Yu norm (DMN-Yu).
Zengbing Xu +4 more
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Learning Neighborhoods for Metric Learning [PDF]
, 2012 Metric learning methods have been shown to perform well on different learning tasks. Many of them rely on target neighborhood relationships that are computed in the original feature space and remain fixed throughout learning. As a result, the learned metric reflects the original neighborhood relations.
Wang Jun +2 more
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REID (Research and Evaluation in Education), 2021 Nowadays, in the pandemic of COVID-19, e-learning systems have been widely used to facilitate teaching and learning processes between lecturers and students.
Sulis Sandiwarno
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Metrics and Continuity in Reinforcement Learning
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 In most practical applications of reinforcement learning, it is untenable to maintain direct estimates for individual states; in continuous-state systems, it is impossible. Instead, researchers often leverage {\em state similarity} (whether explicitly or implicitly) to build models that can generalize well from a limited set of samples.
Charline Le Lan +2 more
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Pacing Electrocardiogram Detection With Memory-Based Autoencoder and Metric Learning
Frontiers in Physiology, 2021 Remote ECG diagnosis has been widely used in the clinical ECG workflow. Especially for patients with pacemaker, in the limited information of patient's medical history, doctors need to determine whether the patient is wearing a pacemaker and also ...
Zhaoyang Ge +9 more
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Object Tracking With Structured Metric Learning
IEEE Access, 2019 In this paper, we propose a novel tracking method based on structured metric learning, which takes the advantages of both structured learning and distance metric learning.
Xiaolin Zhao +4 more
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Ground Metric Learning on Graphs [PDF]
Journal of Mathematical Imaging and Vision, 2020 Optimal transport (OT) distances between probability distributions are parameterized by the ground metric they use between observations. Their relevance for real-life applications strongly hinges on whether that ground metric parameter is suitably chosen.
Heitz, Matthieu +4 more
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IEEE Access, 2021 Many object re-identification (Re-ID) methods that depend on large-scale training datasets have been proposed in recent years. However, the performance of these methods degrades dramatically when insufficient training data are available.
Sheng-Hung Fan +3 more
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