Dec 5, 2017 · Abstract:Johnson-Lindenstrauss embeddings are widely used to reduce the dimension and thus the processing time of data.

Mar 23, 2021 · Johnson–Lindenstrauss embeddings are widely used to reduce the dimension and thus the processing time of data.

The double circulant matrix mimics the behavior of a Gaussian matrix in two important ways: first, it maps an arbitrary set in $\mathbb{R}^n$ into a set of ...

We introduce a new fast construction of a Johnson-Lindenstrauss matrix based on the composition of the following two embeddings: A fast construction by the ...

Jul 29, 2020 · Abstract. Johnson–Lindenstrauss embeddings are widely used to reduce the dimension and thus the processing time of data.

Feb 2, 2024 · I've personally had a lot of success using gte-tiny. This will generate embeddings much faster, produce higher quality embeddings, plus you ...

Optimal fast johnson–lindenstrauss embeddings for large data sets. Sampling Theory, Signal Process- ing, and Data Analysis, 19(1):3, 2021. doi: 10.1007 ...

Mar 23, 2021 · Abstract. Johnson–Lindenstrauss embeddings are widely used to reduce the dimension and thus the processing time of data.

Our main result states that any set of N = exp(Õ(n)) real vectors in n dimensional space can be linearly mapped to a space of dimension k = O(log N polylog ...

Unit M15: Applied Numerical Analysis and Optimization and Data Analysis ... Also, the matrices from Johnson-Lindenstrauss embeddings have interesting properties ...