On Approximation Guarantees for Greedy Low Rank Optimization.
Rajiv KhannaEthan R. ElenbergAlexandros G. DimakisJoydeep GhoshSahand N. NegahbanPublished in: ICML (2017)
Keyphrases
- low rank
- greedy algorithm
- approximation guarantees
- convex optimization
- linear combination
- matrix completion
- matrix factorization
- missing data
- low rank matrix
- singular value decomposition
- rank minimization
- search algorithm
- high order
- high dimensional data
- kernel matrix
- semi supervised
- convex relaxation
- optimization problems
- greedy algorithms
- objective function
- norm minimization
- collaborative filtering
- dynamic programming
- feature extraction
- data sets
- approximation algorithms
- trace norm