PDF] Locality-sensitive binary codes from shift-invariant kernels
Por um escritor misterioso
Last updated 29 julho 2024
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://d3i71xaburhd42.cloudfront.net/1b20afbd2d2a349737ed3dc246e44bbdba203190/8-Figure4-1.png)
This paper introduces a simple distribution-free encoding scheme based on random projections, such that the expected Hamming distance between the binary codes of two vectors is related to the value of a shift-invariant kernel between the vectors. This paper addresses the problem of designing binary codes for high-dimensional data such that vectors that are similar in the original space map to similar binary strings. We introduce a simple distribution-free encoding scheme based on random projections, such that the expected Hamming distance between the binary codes of two vectors is related to the value of a shift-invariant kernel (e.g., a Gaussian kernel) between the vectors. We present a full theoretical analysis of the convergence properties of the proposed scheme, and report favorable experimental performance as compared to a recent state-of-the-art method, spectral hashing.
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://ars.els-cdn.com/content/image/1-s2.0-S0031320318304187-gr1.jpg)
Fixed-length asymmetric binary hashing for fingerprint verification through GMM-SVM based representations - ScienceDirect
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://d3i71xaburhd42.cloudfront.net/b3f09ea2a8cc1d82c2b27d71dd8f7451d178beaf/5-Figure4-1.png)
PDF] Iterative quantization: A procrustean approach to learning binary codes
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://www.mdpi.com/mathematics/mathematics-10-02110/article_deploy/html/images/mathematics-10-02110-g001.png)
Mathematics, Free Full-Text
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PDF] Locality-sensitive binary codes from shift-invariant kernels
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41524-023-01073-w/MediaObjects/41524_2023_1073_Fig1_HTML.png)
Performance of two complementary machine-learned potentials in modelling chemically complex systems
Lensless inference camera: incoherent object recognition through a thin mask with LBP map generation
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://dfzljdn9uc3pi.cloudfront.net/2021/cs-576/1/fig-1-full.png)
Full depth CNN classifier for handwritten and license plate characters recognition [PeerJ]
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://dl.acm.org/cms/asset/22371fdd-3f18-428c-83db-25b58cceb8af/tois-2022-0329-f12.jpg)
Invariant Node Representation Learning under Distribution Shifts with Multiple Latent Environments
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Convolution neural network with batch normalization and inception-residual modules for Android malware classification
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Sensors, Free Full-Text
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