IDAE: Imputation-boosted Denoising Autoencoder for Collaborative Filtering.
Jae-woong LeeJongwuk LeePublished in: CIKM (2017)
Keyphrases
- denoising
- collaborative filtering
- image denoising
- recommender systems
- missing values
- missing data
- noisy images
- natural images
- matrix factorization
- image processing
- maximum margin matrix factorization
- total variation
- wavelet domain
- data sparsity
- missing data imputation
- recommendation systems
- gaussian noise
- user preferences
- transfer learning
- data imputation
- random forests
- noise removal
- denoising algorithm
- wavelet denoising
- deal with information overload
- latent factor models
- recommendation algorithms
- personalized recommendation
- denoising methods
- wavelet packet
- user profiles
- artificial neural networks
- netflix prize
- probabilistic matrix factorization
- cold start problem
- content based filtering
- high dimensional
- social networks
- data sets