3 expos=?iso-8859-15?Q?=E9s_?=de Mark Jonhson (Macquarie University)

[Pascal Amsili]

Bonjour,

De passage à Paris, Mark Jonhson va donner 3 exposés dans les semaines
qui viennent: 

   10th Sept, ENS, Institut d'Etude de la Cognition
      12h: Synergies in Language Acquisition
   12th Sept, LingLunch, Université Paris Diderot
      12h: Language acquisition as statistical inference
   20th Sept, séminaire Alpage, University Paris Diderot
      11h: Grammars and Topic Models

Résumés et détails pratiques sont donnés ci-dessous.

Cordialement,
P. Amsili

----------------------------------------------------------------------
*
*
*Synergies in Language Acquisition**
**
**Mark Johnson**
**Macquarie University**
**
**noon, 10th September**, ENS*

  ENS, Colloquium de L'institut d'Etude de la Cognition
  12h à 13h30,
  salle Langevin, 29 rue d'Ulm, 75005 Paris
  http://www.cognition.ens.fr/ColloquiumIEC.html

Each human language contains an unbounded number of different 
sentences.  How can something so large and complex possibly be learnt?  
Over the past two decades we've learned how to define probability 
distributions over grammars and the linguistic structures they generate, 
making it possible to define statistical models that learn regularities 
of complex linguistic structures. Bayesian approaches are particularly 
attractive because they can exploit "prior" (e.g., innate) knowledge as 
well as learn statistical generalizations from the input.  Here we use 
computational models to investigate "synergies" in language acquisition, 
where a "joint model" is capable of solving "chicken-and-egg" problems 
that are challenging for conventional "staged learning" models.


*
*
*Language acquisition as statistical inference**
**
**Mark Johnson**
**Macquarie University**
**
**noon, 12th September, LingLunch*

  Linglunch Paris Diderot
  Thursday, 12th septembre 2013
  12h-13h, salle 103 
  bâtiment Olympe de Gouges
  (8) rue Albert Einstein, 75013
  http://www.linguist.univ-paris-diderot.fr/linglunch.html

This talk argues that language acquisition -- in particular, syntactic 
parameter setting -- is profitably viewed as a statistical inference 
problem.  I discuss some issues associated with statistical inference 
that linguists might be concerned about, including the possibility of 
"Zombie" parameter settings.  The bulk of the talk focuses on estimating 
parameters in a Stabler-style Minimalist Grammar framework.  Building on 
recent results of Hunter and Dyer (2013), we show how estimating weights 
associated with lexical entries -- including the empty functional 
categories that control parametric syntactic variation -- can be reduced 
to estimating weights in what appears to be a new grammar formalism 
called "feature-weighted context-free grammars", which is a MaxEnt 
generalisation of the "tied context-free grammars" of Headden et al 
(2009).  Importantly, the partition function and its derivatives of a 
feature-weighted context-free grammar can be calculated using a 
generalisation inspired by the Inside-Outside algorithm of the 
algorithms for calculating partition functions in Nederhof and Satta 
(2009).  We show how this can be used to learn lexical entries and verb 
movement and XP movement parameters in three toy corpora.


*
*
*Grammars and Topic Models**
**
**Mark Johnson**
**Macquarie University**
**
**11am, 20th September, Alpage Group*

  Séminaire ALPAGE
  Friday, 20th september, 11h-12h30
  salle 127
  bâtiment Olympe de Gouges
  (8) rue Albert Einstein, 75013
  https://www.rocq.inria.fr/alpage-wiki/tiki-index.php?page=seminaire

Context-free grammars have been a cornerstone of theoretical computer 
science and computational linguistics since their inception over half a 
century ago.  Topic models are a newer development in machine learning 
that play an important role in document analysis and information 
retrieval.  It turns out there is a surprising connection between the 
two that suggests novel ways of extending both grammars and topic 
models.  After explaining this connection, I go on to describe 
extensions which identify topical multiword collocations and 
automatically learn the internal structure of named-entity phrases. 
These new models have applications in text data mining and information 
retrieval.


------------------------------------

Pour se desinscire, envoyer un mel à parislinguists-unsubscribe at yahoogroups.com
Pour s'inscrire, envoyer un mel à parislinguists-subscribe at yahoogroups.comLiens Yahoo! Groupes

<*> Pour consulter votre groupe en ligne, accédez à :
    http://fr.groups.yahoo.com/group/parislinguists/

<*> Vos options mail :
    Mail individuel | Traditionnel

<*> Pour modifier vos options avec le Web, allez sur :
    http://fr.groups.yahoo.com/group/parislinguists/join
    ((Compte Yahoo! requis) 

<*> Pour modifier vos options par mail :
    parislinguists-digest at yahoogroupes.fr 
    parislinguists-fullfeatured at yahoogroupes.fr

<*> Pour vous désincrire de ce groupe, envoyez un mail à :
    parislinguists-desabonnement at yahoogroupes.fr

<*> L'utilisation de Yahoo! Groupes est soumise à l'acceptation des :
    http://info.yahoo.com/legal/fr/yahoo/utos/terms/