coded up icf trainer, haven't tested yet.
added primitive persistence functions for ccv_icf training

I am starting to thinking about a systematic way of doing persistence while training
icfcreate pre learn runs now.
make the icf resume works
fix a mistake on using liblinear, it turns out the weight returned by
liblinear needs to compare with each other (as it is multi-class
classifier in nature), thus, for two class classification, and you want
to use 0 as the threshold, what you really want is w[class1] - w[class2]
as the final weight.
icfcreate finally runs correctly on pedestrian data
speed up icfcreate
the precomputed data is stable enough to give us overall rate as well for icf
fix a bug in ccv_array_new that forbid us to allocate memory that is bigger than 2G
this is not going anywhere, I am going to restart icf
still rewrite most part of icf implementation, but confirmed rate
matched generated rate from depth-2 tree
I think that I got all details of depth-2 tree impl ironed out, but will
run a side-by-side comparison (the _ccv_icf_rate_weak_classifier with
_ccv_icf_find_best_weak_classifier) to make sure the precomputed results
are used correctly.
remove _ccv_icf_rate_weak_classifier as I am pretty confident on the
implementation now, will work on bootstrapping tmrw. Going to bed now.
now bootstrapping works, and fixed persistence issue with classifier
fix precomputed persistence problem
using libdispatch to speed up training
still hit by sharp corner of alloca
make soft cascading work
fix a memory access violation in icf
fix a few places related to feature / example generation, also, try to cap memory usage when precomputing