4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CR2026
Privacy-Preserving Product-Quantized Approximate Nearest Neighbor Search Framework for Large-scale Datasets via A Hybrid of Fully Homomorphic Encryption and Trusted Execution Environment
Shozo Saeki, Minoru Kawahara, Hirohisa Aman
A nearest-neighbor framework is a fundamental tool for various applications involving Large Language Models (LLMs) and Visual Language Models (VLMs). Vectors used for nearest-neigh…
cs.CV2025
Combined Hyperbolic and Euclidean Soft Triple Loss Beyond the Single Space Deep Metric Learning
Shozo Saeki, Minoru Kawahara, Hirohisa Aman
Deep metric learning (DML) aims to learn a neural network mapping data to an embedding space, which can represent semantic similarity between data points. Hyperbolic space is attra…
cs.CV2021★ 4 cited
Multi Proxy Anchor Family Loss for Several Types of Gradients
Shozo Saeki, Minoru Kawahara, Hirohisa Aman
The deep metric learning (DML) objective is to learn a neural network that maps into an embedding space where similar data are near and dissimilar data are far. However, convention…