fix subgradient batch bug and add a test
subgradient test: add another check
Merge pull request #111 from martinsch/subgradient_batch_fix

fix subgradient batch bug and add a test
remove train_test_split backport. It wasn't used consistently and sklearn refactoring breaks the current backport.
Remove error in __repr__ when n_states is none.
Doc fix: lp solver uses cvxopt, not glpk any more.
require relatively recent sklearn, add scipy requirement.
trying install matrix on travis
Use less threads for compiling opengm.
starting on max-product. first, testing if tree or not.

simplify is_tree procedure, test using mst.

slight refactoring (make n_vertices optional in is_tree, introduce edges_to_graph, start on message passing

tree max-product is working (omg?!)

misc fix in finding edge

test with non-repeating pairwise potentials

added tree test, not working :-/ small fixes

finally working on trees.... stupid me...

iterative max-product works

slight refactoring, include max-product in inference dispatch

add damping, stopping tolerance to max-product

example plotting potts model on grid, showing off different infernce algorithms

FIX: add relaxed keyword to inference_max_product.

upgrade tests for new version.
rename mp to max_product, add to inference method list
add lars' viterbi
add lars' viterbi
add benchmarks
add "is_forest" function in pure python
add random tree benchmark
fixed tree max_product
skip tree tests on old scipy
fix mixing long and int in linear programming
remove pyqpbo dependency for easier build.