Johnson-Lindenstrauss embeddings for noisy vectors - taking advantage of the noise.
Zhen ShaoPublished in: CoRR (2022)
Keyphrases
- johnson lindenstrauss
- noisy data
- vector space
- noise free
- noisy environments
- low snr
- measurement noise
- high noise
- missing data
- low signal to noise ratio
- noise level
- signal to noise ratio
- additive noise
- noise reduction
- feature vectors
- input data
- hilbert space
- noisy observations
- low dimensional
- noise model
- random noise
- noise removal
- image noise
- covariance matrices
- manifold learning
- maximum likelihood
- denoising