HMLasso: Lasso for High Dimensional and Highly Missing Data.
Masaaki TakadaHironori FujisawaTakeichiro NishikawaPublished in: CoRR (2018)
Keyphrases
- missing data
- high dimensional
- variable selection
- noisy data
- missing values
- incomplete data
- low rank
- feature selection
- generalized linear models
- structure from motion
- motion segmentation
- multiple imputation
- low dimensional
- feature space
- similarity search
- imprecise data
- high dimensionality
- neural network
- high dimensional data
- least squares
- regression model
- cross validation
- sparse representation
- model selection
- categorical attributes
- dimensionality reduction
- nearest neighbor
- data sets
- missing information
- dirichlet process mixture models
- data imputation
- dimension reduction
- sample size
- probabilistic model
- recommender systems
- feature extraction