The Benefits of Learning with Strongly Convex Approximate Inference

By Ben London, Bert Huang, Lise Getoor. 2015

8 citations recorded by the source corpus.

Subfields: Optimization & Training

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Optimization & Training

1. Simon Lacoste-Julien
2. David A. Sontag
3. Rahul G. Krishnan
4. Peter Richtárik
5. Francis R. Bach
6. Fabian Pedregosa
7. Gauthier Gidel
8. Martin Jaggi

Citations in the corpus

• Barrier Frank-Wolfe for Marginal Inference (2015, background): “The primal objective plus the (approximate) duality gap may no longer be an upper bound on the log-partition function (black-box MAP solvers could be considered to optimize over an inner bound to the marginal polytope).”