N12-4003 research scientist at the Center for Computational Learning Systems in Columbia University
P13-2151 previous studies by applying a computational learning model of phonotactic word segmentation
J94-3007 Metrical Phenomena Recently , computational learning models that specifically address
N12-4003 research scientist at the Center for Computational Learning Systems , Columbia University
P06-2013 Risk Minimization principle from computational learning theory ( Vapnik , 1995 ) . Kudo
W01-0720 simpler problems . 1 Introduction Computational learning of natural language can be considered
W00-0743 The Acquisition of Word Order a Computational Learning System </title> Aline Abstract
P12-2032 Brooklyn , NY , USA 3 Center for Computational Learning Systems , Columbia University
P15-5003 Research Scientist at the Center for Computational Learning Systems at Columbia University
P11-1159 Watson Research Center Center for Computational Learning Systems Abstract We explore the
J13-1008 while he was at the Center for Computational Learning Systems at Columbia University
P93-1024 acquisition both from psychological and computational learning perspectives . From the practical
W02-2033 test this approach , we use a computational learning system , and the results obtained
W01-0720 Stephen Watkinson Suresh Abstract Computational learning of natural language is often
S10-1048 have strong justifications from computational learning theory . MP-BOOST is a Proceedings
P94-1024 rigorous bridge between modern computational learning theory and computational lin
W02-2033 perform an experiment using a computational learning system that receives as input
W00-0743 acquisition from data . We are using a computational learning system that is composed of a
P07-1093 affilated with the Center for Computational Learning Systems , Columbia Uni - versity
W00-1214 minimization principle from the computational learning theory , SVM seeks a decision
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