Results 11 to 20 of about 6,372,670 (283)
Unsupervised Learning of Shape Manifolds [PDF]
Procedings of the British Machine Vision Conference 2007, 2007 Classical shape analysis methods use principal component analysis to reduce the dimensionality of shape spaces. The basic assumption behind these methods is that the subspace corresponding to the major modes of variation for a particular class of shapes is linearised. This may not necessarily be the case in practice.
Nasir M. Rajpoot +2 more
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Unsupervised learning of generative topic saliency for person re-identification [PDF]
, 2014 (c) 2014. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.© 2014. The copyright of this document resides with its authors.
Wang, H +5 more
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Unsupervised two-class and multi-class support vector machines for abnormal traffic characterization [PDF]
, 2009 Although measurement-based real-time traffic classification has received considerable research attention, the timing constraints imposed by the high accuracy requirements and the learning phase of the algorithms employed still remain a challenge. In this
Hutchison, D. +3 more
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Unsupervised Tokenization Learning
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 In the presented study, we discover that the so-called "transition freedom" metric appears superior for unsupervised tokenization purposes in comparison to statistical metrics such as mutual information and conditional probability, providing F-measure scores in range from 0.71 to 1.0 across explored multilingual corpora.
Anton Kolonin, Vignav Ramesh
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Unsupervised Learning for Parametric Optimization [PDF]
IEEE Communications Letters, 2021 This work was supported by the European Research Council under the H2020 Framework Programme/ERC grant agreement 694974, by the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) as well as by MINECO’s Projects RTI2018-102112 and RTI2018-101040, and by the ICREA Academia program.
Rasoul Nikbakht +2 more
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IEEE Access, 2023 In order to solve the resource allocation problem in scenarios of centralized wireless cellular communication with multiple cells, users and channels, a novel resource allocation algorithm based on joint Deep Deterministic Policy Gradient (DDPG ...
Ming Sun +3 more
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IET Cyber-systems and Robotics, 2022 Particle image velocimetry (PIV) is an essential method in experimental fluid dynamics. In recent years, the development of deep learning‐based methods has inspired new approaches to tackle the PIV problem, which considerably improves the accuracy of PIV.
Yiwei Chong +4 more
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Micromachines, 2022 Neuromorphic computing has shown great advantages towards cognitive tasks with high speed and remarkable energy efficiency. Memristor is considered as one of the most promising candidates for the electronic synapse of the neuromorphic computing system ...
Ruiyi Li +7 more
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Unsupervised two-class & multi-class support vector machines for abnormal traffic characterization. [PDF]
, 2009 Although measurement-based real-time traffic classification has received considerable research attention, the timing constraints imposed by the high accuracy requirements and the learning phase of the algorithms employed still remain a challenge. In this
Kim, Hyun-chul +7 more
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Unsupervised Learning of Particles Dispersion
Mathematics, 2023 This paper discusses using unsupervised learning in classifying particle-like dispersion. The problem is relevant to various applications, including virus transmission and atmospheric pollution.
Nicholas Christakis, Dimitris Drikakis
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