Results 11 to 20 of about 1,974,250 (242)
Sparse Matrix-based Random Projection for Classification
, 2013 As a typical dimensionality reduction technique, random projection has been widely applied in a variety of fields concerning categorization. The construction of random projection has also been deeply studied, based on the principle of preserving the ...
Li, Weiyu +3 more
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Orthogonal random projection for tensor completion
IET Computer Vision, 2020 The low‐rank tensor completion problem, which aims to recover the missing data from partially observable data. However, most of the existing tensor completion algorithms based on Tucker decomposition cannot avoid using singular value decomposition (SVD ...
Yali Feng, Guoxu Zhou
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Random projection tree similarity metric for SpectralNet
Array, 2023 SpectralNet is a graph clustering method that uses neural network to find an embedding that separates the data. So far it was only used with k-nn graphs, which are usually constructed using a distance metric (e.g., Euclidean distance).
Mashaan Alshammari +3 more
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CoRR, 2020 We introduce a novel random projection technique for efficiently reducing the dimension of very high-dimensional tensors. Building upon classical results on Gaussian random projections and Johnson-Lindenstrauss transforms~(JLT), we propose two tensorized random projection maps relying on the tensor train~(TT) and CP decomposition format, respectively ...
Beheshteh T. Rakhshan +1 more
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Multimodal Biometric Template Protection Based on a Cancelable SoftmaxOut Fusion Network
Applied Sciences, 2022 Authentication systems that employ biometrics are commonplace, as they offer a convenient means of authenticating an individual’s identity. However, these systems give rise to concerns about security and privacy due to insecure template management.
Jihyeon KIM +2 more
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IEEE Access, 2021 Many researchers are inspired by studying Speech Emotion Recognition (SER) because it is considered as a key effort in Human-Computer Interaction (HCI).
Hemin Ibrahim +2 more
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Random projections of random manifolds
CoRR, 2016 45 pages, 9 ...
Subhaneil Lahiri +2 more
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Random Projections of Smooth Manifolds [PDF]
Foundations of Computational Mathematics, 2007 Consider a compact \(K\)-dimensional Riemannian submanifold \({\mathcal M} \subset\mathbb R^N\) and denote by \(\Phi\) a random orthoprojection operator from \(\mathbb R^N\) onto \(\mathbb R^M\). The main theorem of this article states that with probability at least \(1-\rho\) the distance (or geodesic distance) between any two points \(x\), \(y\in ...
Richard G. Baraniuk, Michael B. Wakin
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Random Projection Neural Network Approximation [PDF]
, 2018 Neural networks are often used to approximate functions defined over high-dimensional data spaces (e.g. text data, genomic data, multi-sensor data). Such approximation tasks are usually difficult due to the curse of dimensionality and improved methods ...
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Random Projections for Linear Programming [PDF]
Mathematics of Operations Research, 2018 Random projections are random linear maps, sampled from appropriate distributions, which approximately preserve certain geometrical invariants so that the approximation improves as the dimension of the space grows. The well known Johnson-Lindenstrauss lemma states that there are random matrices with surprisingly few rows which approximately preserve ...
Ky Khac Vu +2 more
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