feature set 0.00149037
different features 0.001462416
learning algorithm 0.001433771
probabilistic model 0.001408324
learning figure 0.001368021
estimation model 0.0013569460000000002
regression model 0.001350534
pruning model 0.001331265
trained model 0.001313038
such expressions 0.0013105080000000002
global model 0.00130846
same features 0.001282358
feature function 0.0012805400000000002
model updates 0.0012799730000000002
timation model 0.001274271
model plu 0.001269137
training set 0.001229917
learning problem 0.001228518
single set 0.001223591
test set 0.001211958
effective learning 0.001190629
natural language 0.001182901
complete learning 0.001180935
final set 0.001163871
language generation 0.00116385
target set 0.00116072
structure features 0.001157165
semantic modeling 0.0011539
structural features 0.001132355
coverage features 0.001117242
complexity feature 0.001116379
binary features 0.001114246
possible meanings 0.001111739
possible values 0.0011100519999999998
learning rate 0.0011073559999999999
such phenomena 0.001099382
new approach 0.001098283
head features 0.001096547
logical expressions 0.001095852
specific features 0.001090365
initialization set 0.00108747
logical meaning 0.00108523
example output 0.001079638
semantic parser 0.0010688339999999998
such distributions 0.001065058
possible inputs 0.001060231
ture set 0.001050467
logical expression 0.001049839
possible expres 0.001049029
candidate set 0.001047069
logical form 0.001045664
maximal set 0.0010451800000000002
relative error 0.001041526
such variation 0.001040404
set descriptions 0.001039131
model 0.00103628
set difference 0.001034338
development set 0.0010339540000000001
tial set 0.001030142
first results 0.0010282989999999999
semantic pars 0.001016107
different objects 0.0010151700000000001
set indi 0.001013016
semantic parsers 0.001012205
washington semantic 0.001008419
objects algorithm 9.979770000000002E-4
semantic plurality 9.96097E-4
semantic phe 9.96097E-4
relative order 9.96069E-4
other tasks 9.956589999999999E-4
single output 9.95457E-4
inference algorithm 9.84015E-4
new corpus 9.77757E-4
relative coverage 9.734349999999999E-4
relative reduction 9.71725E-4
type expressions 9.713720000000001E-4
logical forms 9.70631E-4
language instruc 9.598429999999999E-4
ural language 9.598429999999999E-4
problem output 9.5381E-4
feature expectations 9.51966E-4
large number 9.4899E-4
complete system 9.48838E-4
pute feature 9.48354E-4
logical constant 9.42228E-4
small number 9.36515E-4
relative frequency 9.23896E-4
logical representation 9.21053E-4
different approaches 9.18943E-4
other factors 9.076049999999999E-4
expressions domain 9.07075E-4
other strate 9.0559E-4
probability distribution 9.01319E-4
expression generation 8.966009999999999E-4
modeling approach 8.95666E-4
new constants 8.881310000000001E-4
ing sets 8.85553E-4
logical constants 8.855130000000001E-4
modeling meaning 8.85231E-4
recent work 8.78709E-4
