PDF] Locality-sensitive binary codes from shift-invariant kernels
Por um escritor misterioso
Last updated 24 março 2025
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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://ietresearch.onlinelibrary.wiley.com/cms/asset/fe4c965b-7ddb-41e8-a2f1-043bb8bb79ed/cvi2bf00303-fig-0004-m.jpg)
Kernel locality‐constrained sparse coding for head pose estimation - Kim - 2016 - IET Computer Vision - Wiley Online Library
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Evaluation of noise robustness for local binary pattern descriptors in texture classification – topic of research paper in Medical engineering. Download scholarly article PDF and read for free on CyberLeninka open science
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://pub.mdpi-res.com/remotesensing/remotesensing-14-06358/article_deploy/html/images/remotesensing-14-06358-ag.png?1671680125)
Remote Sensing, Free Full-Text
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Locality sensitive hashing with bit selection
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://media.arxiv-vanity.com/render-output/8431871/Figures/graphical_abs.png)
Let's do the time-warp-attend: Learning topological invariants of dynamical systems – arXiv Vanity
Charting Nanocluster Structures via Convolutional Neural Networks
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://iiif.elifesciences.org/lax:78606%2Felife-78606-fig2-v2.tif/full/1500,/0/default.jpg)
Population codes enable learning from few examples by shaping inductive bias
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://img.yumpu.com/11852582/1/500x640/ec-624-digital-image-processing-3-0-2-8-class-i-introduction-.jpg)
EC 624 Digital Image Processing (3 0 2 8) Class I Introduction
![PDF] Locality-sensitive binary codes from shift-invariant kernels](https://i1.rgstatic.net/publication/338003088_Drawbacks_and_Proposed_Solutions_for_Real-time_Processing_on_Existing_State-of-the-art_Locality_Sensitive_Hashing_Techniques/links/5faaf4cc4585150781076bc3/largepreview.png)
PDF) Drawbacks and Proposed Solutions for Real-time Processing on Existing State-of-the-art Locality Sensitive Hashing Techniques
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Artificial neural network - Wikipedia
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Frontiers Quantitative approaches for decoding the specificity of the human T cell repertoire
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Sensors, Free Full-Text
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