few changes to run benchmarks on glm2.
Now have working sparse with DenseColMatrix and SparseVector (ATTENTION: sparse handling is hardcoded!).
GLM2 performance update. Made GLM2 to be as fast as GLM1 in default settings. To get higher accuracy, run with line_search on.
Fix race bug in Quantile, fix Apply bug for frames

Quantiles - didn't block on closing writes.  Also clean up logic in main
loop a bunch.
Apply - if returning a Frame & applying to multi-columns, ref-cnt was
wrong on intermediate frames
Merge branch 'master' of github.com:0xdata/h2o
Make test not throw execptiopn

Expected to catch throw exception
Merge branch 'master' of github.com:0xdata/h2o

Conflicts:
	src/main/java/hex/glm/GLM2.java
Renamed line_search to higher_accuracy.
More test-throw cleanup

DRF does not print stack traces, since tests force them & expect them
Merge branch 'master' of github.com:0xdata/h2o
Add NPE checks.
Cleanup Sparse backprop call.
Merge branch 'master' into arno-deeplearning2

Conflicts:
	src/main/java/hex/deeplearning/DeepLearningModel.java
	src/main/java/hex/deeplearning/DeepLearningTask.java
don't use 100
Merge branch 'master' of github.com:0xdata/h2o
smaller MAX_QBINS to force more iterations
some boundary conditions: all na, single values, etc
add quantilespage request also for these cases
parsing with h2o standalone to cdh5, got java.lang.NoClassDefFoundError: org/apache/commons/io/IOUtils.. apparently IOUtils is in two places in cdh5/hadoop? adding jar (thanks michal)
small dataset that forces iterations (3) even with 1000 bins