May 4, 2023 · Furthermore, a privacy-preserving and communication-efficient mechanism with gradient-quantization technique is presented to train the proposed ...
Unlike distributed methods that collect data centrally and perform training. 1020. Page 3. DGMF for Fast Privacy-Preserving POI Recommendation collaboratively ...
Decentralized Gradient-Quantization Based Matrix Factorization for Fast Privacy-Preserving Point-of-Interest Recommendation ... To read the full-text of this ...
Decentralized Gradient-Quantization Based Matrix Factorization for Fast Privacy-Preserving Point-of-Interest Recommendation ... J. Artif. Intell. Res. 2023. TLDR.
Mar 12, 2020 · To solve these, we present a Decentralized MF (DMF) framework for POI recommendation. Specifically, instead of maintaining all the low rank ...
Missing: Gradient- Quantization
Decentralized Gradient-Quantization Based Matrix Factorization for Fast Privacy-Preserving Point-of-Interest Recommendation · Computer Science. J. Artif. Intell.
Feb 24, 2024 · Decentralized Gradient-Quantization Based Matrix Factorization for Fast Privacy-Preserving Point-of-Interest Recommendation. Article. Apr 2023 ...
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Jun 25, 2024 · Based on these two trees, we design an efficient LBSNs-based and category-aware POI recommendation algorithm to support a threshold POI ...
Nov 2, 2022 · Further, we devise a decentralized learning method that allows users to keep their private data on the end devices. A novel decomposing strategy ...
Missing: Quantization | Show results with:Quantization
Chen, Privacy preserving point-of-interest recommendation using decentralized matrix factorization, с. · Guan, Toward privacy-preserving cybertwin-based ...