Results 11 to 20 of about 6,473,960 (319)
A Quasi-Isometric Embedding Algorithm [PDF]
Pattern Recognition and Image Analysis, 2019 The Whitney embedding theorem gives an upper bound on the smallest embedding dimension of a manifold. If a data set lies on a manifold, a random projection into this reduced dimension will retain the manifold structure.
David W. Dreisigmeyer
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Variational quantum algorithm for node embedding
Fundamental ResearchQuantum machine learning has made remarkable progress in many important tasks. However, the gate complexity of the initial state preparation is seldom considered in lots of quantum machine learning algorithms, making them non-end-to-end.
Zeng-rong Zhou, Hang Li, Gui-Lu Long
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Quantum algorithm for neighborhood preserving embedding [PDF]
Chinese Physics B, 2022 Neighborhood preserving embedding (NPE) is an important linear dimensionality reduction technique that aims at preserving the local manifold structure. NPE contains three steps, i.e., finding the nearest neighbors of each data point, constructing the weight matrix, and obtaining the transformation matrix. Liang et al.
Pan, Shi-Jie +6 more
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Deconstructing word embedding algorithms [PDF]
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 Word embeddings are reliable feature representations of words used to obtain high quality results for various NLP applications. Uncontextualized word embeddings are used in many NLP tasks today, especially in resource-limited settings where high memory capacity and GPUs are not available.
Kenyon-Dean, Kian +2 more
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Enercy Efficient Virtual Network Embedding in Data Center Optical Networks
Guangtongxin yanjiu, 2022 To solve the energy consumption problem in Data Center Optical Networks (DCONs), an Energy Efficient Embedding algorithm based on Matching Network Resources (3E-MNR) scheme is proposed.
Jia-qi NIE
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Spectral Nonlinearly Embedded Clustering Algorithm [PDF]
Mathematical Problems in Engineering, 2016 As is well known, traditional spectral clustering (SC) methods are developed based on themanifold assumption, namely, that two nearby data points in the high-density region of a low-dimensional data manifold have the same cluster label. But, for some high-dimensional and sparse data, such an assumption might be invalid.
Liu, Mingming +3 more
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High Capacity Reversible Data Hiding Algorithm for Audio Files Based on Code Division Multiplexing [PDF]
Jisuanji kexue, 2021 Aiming at the problem of small embedding capacity and low security of reversible data hiding algorithm for audio files,a reversible data hiding(RDH) algorithm for audio files based on code division multiplexing(CDM) is proposed in this paper.The ...
MA Bin, HOU Jin-cheng, WANG Chun-peng, LI Jian, SHI Yun-qing
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Four-round Embedding Reversible Information Hiding Algorithm Based on Median Prediction [PDF]
Jisuanji gongcheng, 2022 Traditional reversible information hiding algorithms based on prediction-error histogram translation primarily use a fixed scanning sequence to scan the original image for data embedding.This method does not consider the texture information of the image ...
REN Fang, XUE Feiyuan, YAO Xuemei
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A word embedding trained on South African news data
The African Journal of Information and Communication, 2022 This article presents results from a study that developed and tested a word embedding trained on a dataset of South African news articles. A word embedding is an algorithm-generated word representation that can be used to analyse the corpus of words ...
Martin Canaan Mafunda +3 more
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Averaging on Manifolds by Embedding Algorithm [PDF]
Journal of Mathematical Imaging and Vision, 2013 We will propose a new algorithm for finding critical points of cost functions defined on a differential manifold. We will lift the initial cost function to a manifold that can be embedded in a Riemannian manifold (Euclidean space) and will construct a vector field defined on the ambient space whose restriction to the embedded manifold is the gradient ...
Birtea, Petre +2 more
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