A Global Geometric Framework for Nonlinear Dimensionality Reduction - Joshua B. Tenenbaum, Vin De Silva, John C. Langford

"A Global Geometric Framework for Nonlinear Dimensionality Reduction" is a research paper written by Joshua B. Tenenbaum, Vin De Silva, and John C. Langford. This paper presents a mathematical framework for reducing the dimensions of complex data in a way that preserves important geometric relationships. It is used in the field of machine learning and data analysis to help understand and visualize high-dimensional data more effectively.

FAQ

Q: Who are the authors of the document?
A: Joshua B. Tenenbaum, Vin De Silva, John C. Langford

Q: What is the purpose of the document?
A: To propose a method for reducing the dimensionality of data

Q: Who is the target audience of the document?
A: Researchers and practitioners working in dimensionality reduction