Scaling and renormalization in high-dimensional regression.
Alexander B. AtanasovJacob A. Zavatone-VethCengiz PehlevanPublished in: CoRR (2024)
Keyphrases
- high dimensional
- regression model
- multi variate
- low dimensional
- high dimensionality
- linear regression
- polynomial regression
- similarity search
- generalized linear models
- locally weighted
- variable selection
- ridge regression
- estimation problems
- regression problems
- dimensionality reduction
- high dimensional problems
- nearest neighbor
- high dimensional data
- metric space
- sparse data
- dimension reduction
- aggregating algorithm
- parameter space
- multi dimensional
- high dimensional spaces
- data points
- manifold learning
- support vector regression
- gaussian processes
- noisy data
- partial least squares
- support vector
- feature vectors
- highly discriminative
- regression algorithm
- high dimensional datasets
- genetic programming
- logistic regression
- model selection