Limitations of convex programming: lower bounds on extended formulations and factorization ranks (Dagstuhl Seminar 15082).
Hartmut KlauckTroy LeeDirk Oliver TheisRekha R. ThomasPublished in: Dagstuhl Reports (2015)
Keyphrases
- convex programming
- lower bound
- convex optimization
- interior point methods
- linear programming
- upper bound
- low rank
- objective function
- kernel learning
- np hard
- primal dual
- convex functions
- total variation
- matrix factorization
- natural images
- semidefinite programming
- optimal solution
- learning algorithm
- max flow
- singular value decomposition