[Lisa_seminaires] [Tea Talk] Timothy O'Donnell (McGill) Fri Jan 19 10:30AM AA1360

Michael Noukhovitch mnoukhov at gmail.com
Ven 19 Jan 10:20:41 EST 2018


Reminder: this is in 10!

On Tue, Jan 16, 2018, 12:56 Michael Noukhovitch <mnoukhov at gmail.com> wrote:

> *Note: *For the new year, we're moving to a different room, *AA1360* on
> the first floor! Exciting!
>
> For the first tea talk of the year we are going to have *Timothy
> O'Donnell*, professor at *McGill,* giving a talk on *Friday Jan 19th* at*
> 10:30AM* in room *AA1360*.
>
> This should be a real gronk of talk, and I'd encourage everyone to attend
> to it!
> Michael
>
> *KEYWORDS *Computational Linguistics, Language Learning, Linguistic
> Structure
>
> *TITLE* Computation, Storage, and Generalization in Language
>
> *ABSTRACT*
> A celebrated property of natural language is creativity, the ability
> to combine stored units to derive new expressions. This feature is
> found across multiple levels of linguistic structure: Sounds can be
> combined to form novel roots, suffixes, and affixes, which can be
> combined to form novel words, which can be combined to form novel
> sentences. However, each human language is characterized by its own
> inventory of units at each level and its own constraints on their
> combination. A syllable like "derp" sounds like a better morpheme of
> English than a syllable like "denp." The existence of the words "warmth"
> and "truth" do not imply the possibility of "coolth," but
> "warmness," "trueness," and "coolness" are all grammatical. And
> speakers of English will naturally drop the phrase "on the counter"
> from "John made dinner on the counter", but not from "John put dinner
> on the counter".
>
> How do learners acquire the inventory of units and constraints at each
> level of linguistic structure that are particular to their own language? I
> will discuss a theoretical framework designed to address this question and
> a number of specific applications. The approach is based on the idea that
> this problem can be approached by formulating a variety of
> linguistic learning problems as problems of program induction and then
> optimizing a tradeoff between a pressure to store fewer, more reusable
> primitive units and a pressure to account for each linguistic expression in
> as few computational steps as possible. Although the idea behind this
> tradeoff is an old one, it has surprisingly deep and
> far-reaching consequences when applied to domain-specific models of
> linguistic computation. I will show how this approach can shed light on a
> number of problems across the linguistic system.
>
>
> *BIO*
> Tim O'Donnell is an assistant professor in the department of
> linguistics at McGill University. Previously he was a research scientist at
> MIT in the department of Brain and Cognitive Sciences.
> His research focuses on developing mathematical and computational models
> of language learning and processing. His work draws on techniques from
> computational linguistics, and artificial intelligence integrating ideas
> from theoretical linguistics and methods from experimental psychology.
>
>
>
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