UNE APPROCHE THEORIQUE DE L'APPRENTISSAGE CONNEXIONNISTE ET APPLICATIONS A LA RECONNAISSANCE DE LA PAROLE PDF Download
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Author: LEON.. BOTTOU
Publisher:
ISBN:
Category :
Languages : fr
Pages :
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LA THESE EXPOSE PLUSIEURS POINTS THEORIQUES CONCERNANT L'APPRENTISSAGE CONNEXIONNISTE, PROVENANT DES MATHEMATIQUES DES ALGORITHMES ADAPTATIFS ET DES STATISTIQUES. CES POINTS SONT DISCUTES A LA LUMIERE DE PROBLEMES PRATIQUES POSES PAR LA RECONNAISSANCE AUTOMATIQUE DE LA PAROLE
Author: LEON.. BOTTOU
Publisher:
ISBN:
Category :
Languages : fr
Pages :
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LA THESE EXPOSE PLUSIEURS POINTS THEORIQUES CONCERNANT L'APPRENTISSAGE CONNEXIONNISTE, PROVENANT DES MATHEMATIQUES DES ALGORITHMES ADAPTATIFS ET DES STATISTIQUES. CES POINTS SONT DISCUTES A LA LUMIERE DE PROBLEMES PRATIQUES POSES PAR LA RECONNAISSANCE AUTOMATIQUE DE LA PAROLE
Author: Satoshi Sekine
Publisher: John Benjamins Publishing
ISBN: 9027222495
Category : Language Arts & Disciplines
Languages : en
Pages : 177
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Book Description
Printbegrænsninger: Der kan printes 10 sider ad gangen og max. 40 sider pr. session
Author: Alexander Gelbukh
Publisher: Springer
ISBN: 3540305866
Category : Computers
Languages : en
Pages : 845
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Book Description
CICLing 2005 (www.CICLing.org) was the 6th Annual Conference on Intelligent Text Processing and Computational Linguistics. It was intended to provide a balanced view of the cutting-edge developments in both the theoretical foundations of computational linguistics and the practice of natural-language text processing with its numerous applications. A feature of CICLing conferences is their wide scope that covers nearly all areas of computational linguistics and all aspects of natural language processing applications. This year we were honored by the presence of our keynote speakers Christian Boitet (CLIPS-IMAG, Grenoble), Kevin Knight (ISI), Daniel Marcu (ISI), and Ellen Riloff (University of Utah), who delivered excellent extended lectures and organized vivid discussions and encouraging tutorials; their invited papers are published in this volume. Of 151 submissions received, 88 were selected for presentation; 53 as full papers and 35 as short papers, by exactly 200 authors from 26 countries: USA (15 papers); Mexico (12); China (9.5); Spain (7.5); South Korea (5.5); Singapore (5); Germany (4.8); Japan (4); UK (3.5); France (3.3); India (3); Italy (3); Czech Republic (2.5); Romania (2.3); Brazil, Canada, Greece, Ireland, Israel, the Netherlands, Norway, Portugal, Sweden, Switzerland (1 each); Hong Kong (0.5); and Russia (0.5) including the invited papers. Internationally co-authored papers are counted in equal fractions.
Author: Patrick Haffner
Publisher:
ISBN:
Category :
Languages : fr
Pages : 255
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CETTE THESE S'INTERESSE AUX PROBLEMES DE L'APPRENTISSAGE DES SEQUENCES TEMPORELLES, POUR DES APPLICATIONS A LA RECONNAISSANCE DE LA PAROLE. ELLE EXPLORE LES POSSIBILITES D'UN APPRENTISSAGE AUSSI GLOBAL QUE POSSIBLE, SANS CHERCHER A INTRODUIRE DE CONNAISSANCES A PRIORI: LE TAUX D'ERREURS DE RECONNAISSANCE EST MINIMISE PAR DES TECHNIQUES D'OPTIMISATIONS (RETROPROPAGATION DU GRADIENT). DES ADAPTATIONS DE L'ARCHITECTURE ET DE L'APPRENTISSAGE CONNEXIONNISTE A LA RECONNAISSANCE DES SEQUENCES SONT PROPOSEES. ELLES SONT COMPAREES, D'UN POINT DE VUE THEORIQUE ET EXPERIMENTAL, AUX MODELES DE MARKOV CACHES OPTIMISES PAR UN MAXIMUM DE VRAISEMBLANCE, QUI REPRESENTENT L'ETAT DE L'ART EN RECONNAISSANCE DE LA PAROLE. SUR DES EXPERIENCES DE RECONNAISSANCE DE LA PAROLE INDEPENDANTE DU LOCUTEUR A TRAVERS LE RESEAU TELEPHONIQUE, NOUS FAISONS LES OBSERVATIONS SUIVANTES: L'IMPLEMENTATION DES MODELES DE MARKOV REPRESENTE UN CAS PARTICULIER DES ARCHITECTURES CONNEXIONNISTES (I.E. RESEAUX A COUCHES) PARTICULIEREMENT SIMPLE ET PERFORMANT. L'APPRENTISSAGE CONNEXIONNISTE (I.E. DISCRIMINANT) PRESENTE UNE ALTERNATIVE AU MAXIMUM DE VRAISEMBLANCE, PLUS FLEXIBLE ET EXIGEANT MOINS DE PARAMETRES. SA PRINCIPALE LIMITATION EST LE MANQUE DE ROBUSTESSE DES CORRESPONDANCES TEMPORELLES APPRISES. DES SOLUTIONS SONT PROPOSEES OU EBAUCHEES POUR Y REMEDIER.
Author: Gulchohra Mammadova
Publisher: Springer Nature
ISBN: 3031734203
Category :
Languages : en
Pages : 417
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Author: Jörg Tiedemann
Publisher: Springer Nature
ISBN: 3031021428
Category : Computers
Languages : en
Pages : 153
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This book provides an overview of various techniques for the alignment of bitexts. It describes general concepts and strategies that can be applied to map corresponding parts in parallel documents on various levels of granularity. Bitexts are valuable linguistic resources for many different research fields and practical applications. The most predominant application is machine translation, in particular, statistical machine translation. However, there are various other threads that can be followed which may be supported by the rich linguistic knowledge implicitly stored in parallel resources. Bitexts have been explored in lexicography, word sense disambiguation, terminology extraction, computer-aided language learning and translation studies to name just a few. The book covers the essential tasks that have to be carried out when building parallel corpora starting from the collection of translated documents up to sub-sentential alignments. In particular, it describes various approaches to document alignment, sentence alignment, word alignment and tree structure alignment. It also includes a list of resources and a comprehensive review of the literature on alignment techniques. Table of Contents: Introduction / Basic Concepts and Terminology / Building Parallel Corpora / Sentence Alignment / Word Alignment / Phrase and Tree Alignment / Concluding Remarks
Author: Ernest K. Ryu
Publisher: Cambridge University Press
ISBN: 1009191063
Category : Mathematics
Languages : en
Pages : 320
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Book Description
Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods – including parallel-distributed algorithms – through the abstraction of monotone operators. With the increased computational power and availability of big data over the past decade, applied disciplines have demanded that larger and larger optimization problems be solved. This text covers the first-order convex optimization methods that are uniquely effective at solving these large-scale optimization problems. Readers will have the opportunity to construct and analyze many well-known classical and modern algorithms using monotone operators, and walk away with a solid understanding of the diverse optimization algorithms. Graduate students and researchers in mathematical optimization, operations research, electrical engineering, statistics, and computer science will appreciate this concise introduction to the theory of convex optimization algorithms.
Author: Association for Computational Linguistics. Meeting
Publisher: Morgan Kaufmann
ISBN:
Category : Computational linguistics
Languages : en
Pages : 584
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Book Description
Philosophers have long been fascinated by the connection between cause and effect: are causes things we can experience or are they concepts provided by our minds? The study of causation goes back to Aristotle, but resurged with David Hume and Immanuel Kant, and is now one of the most important topics in metaphysics. Most of the recent work done in this area has attempted to place causation in a deterministic, scientific worldview. But what about the unpredictable and chancey world we actually live in: can one theory of causation cover all instances of cause and effect?
Author: Stéphane Loiselle
Publisher:
ISBN: 9781412311557
Category : Automatic speech recognition
Languages : fr
Pages : 280
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Author: Martine Roques
Publisher:
ISBN:
Category :
Languages : fr
Pages : 239
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Book Description
L'OBJET DE CETTE THESE EST L'ETUDE DE L'APPRENTISSAGE AUTOMATIQUE DE STRUCTURES SYNTAXIQUES DANS UN SYSTEME CONNEXIONNISTE A PROPAGATION GUIDEE, ET L'EXPLOITATION DE CES STRUCTURES DANS LE CADRE D'UN SYSTEME HOMOGENE DE COMMUNICATION HOMME-MACHINE. CETTE HOMOGENEITE S'EXPRIME PAR L'UTILISATION DES MEMES MECANISMES DE TRAITEMENT POUR DIFFERENTS NIVEAUX D'ABSTRACTION ET POUR DIFFERENTES MODALITES DE COMMUNICATION. DE PLUS, LES PHASES D'APPRENTISSAGE ET DE RECONNAISSANCE NE SONT PAS DISSOCIEES. LE COMPORTEMENT DU RESEAU VARIE EN FONCTION DES VALEURS DES PARAMETRES DE PROPAGATION. L'APPRENTISSAGE DANS CE MODELE EST A PRIORI NON SUPERVISE. LES STRUCTURES SYNTAXIQUES SONT CONSTRUITES A PARTIR DE CORPUS D'ENONCES EN LANGAGE NATUREL. TROIS STRATEGIES D'APPRENTISSAGE PAR HIERARCHISATION DES RESEAUX SONT ETUDIEES AFIN D'AMELIORER LA QUALITE ET LA CONCISION DES REPRESENTATIONS. LE TRAITEMENT DE FORMES INATTENDUES EST REALISE PAR LA CREATION DE NOUVELLES STRUCTURES OU PAR L'ADAPTATION DES STRUCTURES EXISTANTES, SUIVANT LA VALEUR DES PARAMETRES DE PROPAGATION. LES REPRESENTATIONS OBTENUES SONT EXPLOITABLES DE DIFFERENTES FACONS: POUR L'ANALYSE DES PHRASES, SOUS LA FORME DE SEQUENCES DE CLASSES LEXICALES; POUR LA RECONNAISSANCE DE STRUCTURES INCONNUES OU DEFORMEES; POUR LA SEGMENTATION DE LA PAROLE CONTINUE, PAR PREDICTION DE CLASSES. LE SYSTEME OBTENU PARTICIPERA A L'ANALYSE STRUCTURELLE DES ENONCES EN LANGAGE NATUREL TRAITES DANS LE SYSTEME DE COMMUNICATION HOMME-MACHINE A PROPAGATION GUIDEE
