informational complexity learning kluwer academic publishers proud announce publication informational complexity learning perspectives neural networks generative grammar partha niyogi massachusetts institute technology among topics informational complexity learning perspectives neural networks generative grammar brings together two important different learning problems within analytical framework first concerns problem learning functional mappings using neural networks followed learning natural language grammars principles parameters tradition chomsky two learning problems seemingly different neural networks realvalued infinitedimensional continuous mappings hand grammars booleanvalued finitedimensional discrete symbolic mappings book objective bridge gap uses formal techniques developed statistical learning theory theoretical computer science last decade analyze kinds learning problems specific results include model selection neural networks active learning language learning evolutionary models language change informational complexity learning perspectives neural networks generative grammar interdisciplinary work individuals interested interaction computer science cognitive science enjoy book researchers artificial intelligence neural networks linguistics theoretical computer science statistics find particularly relevant contents foreword preface 1 introduction 2 generalization error neural nets 3 active learning 4 language learning 5 language change 6 conclusions 1998 248 pp isbn 07923 8081 9 98 00 information publication please visit line catalogue http www wkap nl may order directly kluwer academic publishers 101 philip drive norwell 02061 phone 781871 6600 fax 781 8716528 e mail kluwer wkap com kluwer academic publishers p box 322 3300 ah dordrecht netherlands phone 31 78 639 2392 fax 31 78 6546474 e mail services wkap nl