On Approximation Guarantees for Greedy Low Rank Optimization.
Rajiv KhannaEthan R. ElenbergAlexandros G. DimakisSahand N. NegahbanPublished in: CoRR (2017)
Keyphrases
- low rank
- greedy algorithm
- approximation guarantees
- convex optimization
- matrix factorization
- missing data
- linear combination
- singular value decomposition
- matrix completion
- rank minimization
- low rank matrix
- semi supervised
- approximation algorithms
- high order
- trace norm
- high dimensional data
- np hard
- optimization problems
- small number
- dynamic programming
- kernel matrix
- greedy algorithms
- feature selection
- convex relaxation
- pairwise
- reinforcement learning
- collaborative filtering