No âmbito da 3ª edição do Ciclo de Palestras por Jovens Doutorados (DEEC-JD3), irá realizar-se no próximo dia 11 de março de 2020, às 12:00, no anfiteatro EA2, a 4ª palestra do ciclo.

(ADIADA PARA DATA A ANUNCIAR)

Título: Learning to Represent Variation in Linguistic Data.

Orador: Wilker Aziz, Professor Auxiliar em "computational linguistics" na Universidade de Amsterdão

Abstract: A defining feature of natural languages is variation: ideas can be expressed in different ways; different words mean the same; the same words mean differently. There's variation that's inherent to linguistic devices (morphology, syntax, discourse), there's variation due to background of the speaker, there's variation that's used to convey opinions and/or imbue one with emotions, there's variation due to seemly arbitrary confounders such as fatigue, concentration level, and boredom. Despite this unavoidable truth, many of the state-of-the-art models for natural language processing cannot account for unobserved factors of variation, instead conflating such factors under a single hypothesis. In this talk he will discuss how to equip these models with statistical tools that promote an explicit account of variation and demonstrate a few applications aimed at different levels of linguistic variability (e.g. sentence-level, word-level, and subword-level). He will close the talk with thoughts on the role of inductive biases such as multimodality and sparsity in the learning of disentangled factors of variation.