Algorithms · Nonlinear Dimensionality Reduction and Manifold Learning

TitleAuthors
Dimensionality reduction: theoretical perspective on practical measuresYair Bartal · Nova Fandina · Ofer Neiman
Learning nonlinear level sets for dimensionality reduction in function approximationGuannan Zhang · Jiaxin Zhang · Jacob Hinkle
No Pressure! Addressing the Problem of Local Minima in Manifold Learning AlgorithmsMax Vladymyrov
Selecting the independent coordinates of manifolds with large aspect ratiosYu-Chia Chen · Marina Meila
Subspace Detours: Building Transport Plans that are Optimal on Subspace ProjectionsBoris Muzellec · Marco Cuturi
Unsupervised Co-Learning on G-Manifolds Across Irreducible RepresentationsYifeng Fan · Tingran Gao · Zhizhen Jane Zhao