For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions

11 March 2021

Papers citing "For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions"

6 / 6 papers shown

Title
A Theoretical Study of Neural Network Expressive Power via Manifold Topology Jiachen Yao Mayank Goswami Chao Chen 52 0 0 21 Oct 2024
Manifold Learning via Foliations and Knowledge Transfer E. Tron E. Fioresi 37 1 0 11 Sep 2024
Randomly Weighted Neuromodulation in Neural Networks Facilitates Learning of Manifolds Common Across Tasks Jinyung Hong Theodore P. Pavlic 38 0 0 17 Nov 2023
A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge Le Ma Ran Zhang Yikun Han Shirui Yu Zaitian Wang ... Pengfei Wang Yanjie Fu Chunjiang Liu Yuanchun Zhou Chang-Tien Lu 100 64 0 18 Oct 2023
Fitting an immersed submanifold to data via Sussmann's orbit theorem Joshua Hanson Maxim Raginsky 71 4 0 03 Apr 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features Jinxin Zhou Xiao Li Tian Ding Chong You Qing Qu Zhihui Zhu 78 102 0 02 Mar 2022