Results 11 to 20 of about 136,861 (303)
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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Anomaly Detection in Blockchain Networks Using Unsupervised Learning: A Survey
AlgorithmsIn decentralized systems, the quest for heightened security and integrity within blockchain networks becomes an issue. This survey investigates anomaly detection techniques in blockchain ecosystems through the lens of unsupervised learning, delving into ...
Christos Cholevas +4 more
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Unsupervised learning and generalization [PDF]
Proceedings of International Conference on Neural Networks (ICNN'96), 2002 The concept of generalization is defined for a general class of unsupervised learning machines. The generalization error is a straightforward extension of the corresponding concept for supervised learning, and may be estimated empirically using a test set or by statistical means-in close analogy with supervised learning.
Lars Kai Hansen, Jan Larsen
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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 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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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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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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Stable and Fast Deep Mutual Information Maximization Based on Wasserstein Distance
Entropy, 2023 Deep learning is one of the most exciting and promising techniques in the field of artificial intelligence (AI), which drives AI applications to be more intelligent and comprehensive.
Xing He +4 more
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Deep boundary‑aware clustering by jointly optimizing unsupervised representation learning [PDF]
, 2022 Deep clustering obtains feature representation generally and then performs clustering for high dimension real-world data. However, conventional solutions are two-stage embedding learning-based methods and these two processes are separate and independent,
Li, Lin +4 more
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Unsupervised Learning of Monocular Depth Estimation:A Survey [PDF]
Jisuanji kexueAs the key point of 3D reconstruction,automatic driving and visual SLAM,depth estimation has always been a hot research direction in the field of computer vision,among which,monocular depth estimation technology based on unsupervised learning has been ...
CAI Jiacheng, DONG Fangmin, SUN Shuifa, TANG Yongheng
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