Search Results for author:
Found 2 papers, 1 papers with code
Scalable manifold learning by uniform landmark sampling and constrained locally linear embedding
As a pivotal approach in machine learning and data science, manifold learning aims to uncover the intrinsic low-dimensional structure within complex nonlinear manifolds in high-dimensional space.
Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking
In this work, we propose a Dynamic Visual Semantic Sub-Embeddings framework (DVSE) to reduce the information entropy.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
