Results 151 to 160 of about 822,037 (305)
Efficient Model-free Reinforcement Learning in Metric Spaces [PDF]
, 2019 Zhao Song, Wen Sun
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M$^5$L: Multi-Modal Multi-Margin Metric Learning for RGBT Tracking [PDF]
, 2020 Zhengzheng Tu +4 more
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Constraint selection in metric learning
Knowledge-Based Systems, 2018 A number of machine learning algorithms are using a metric, or a distance, in order to compare individuals. The Euclidean distance is usually employed, but it may be more efficient to learn a parametric distance such as Mahalanobis metric. Learning such a metric is a hot topic since more than ten years now, and a number of methods have been proposed to
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Clinically Relevant Outcome Measures in Women With Adrenoleukodystrophy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Adrenoleukodystrophy is a rare inherited peroxisomal disease caused by pathogenic variants in the ABCD1 gene located on the X chromosome. Although the most severe central nervous system and adrenal complications typically affect only men with adrenoleukodystrophy, the majority of women develop myeloneuropathy symptoms in adulthood.
Chenwei Yan +3 more
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Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source
Towards Adversarial Robustness for Multi-Mode Data through Metric Learning. [PDF]
Sensors (Basel), 2023 Khan S, Chen JC, Liao WH, Chen CS.
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Evaluation Metrics of Electronic Learning Resources Quality
, 2009 Hennadiy Kravtsov
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Quantifying Learning and Competition among Crowdfunding Projects: Metrics and a Predictive Model
, 2023 Christina Erler +2 more
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Technical report: Impact of evaluation metrics and sampling on the comparison of machine learning methods for biodiversity indicators prediction [PDF]
, 2021 Geneviève Robin, Cathia Le Hasif
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction Progressive Supranuclear Palsy (PSP) is a neurodegenerative ‘tauopathy’ with predominating pathology in the basal ganglia and midbrain. Caudal tau spread frequently implicates the cerebellum; however, the pattern of atrophy remains equivocal.
Chloe Spiegel +8 more
wiley +1 more source