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URL:/computer-science/events/phd-defence-ml-nlp-less-is
 -more-restricted-representations-for-better-interpretability-and-generaliz
 ability
SUMMARY:PhD Defence • Machine Learning | Natural Language Processing •\
 nLess is More: Restricted Representations for Better Interpretability\nand
  Generalizability
CLASS:PUBLIC
DESCRIPTION:Summary \n\nPLEASE NOTE: THIS PHD DEFENCE WILL TAKE PLACE ONLIN
 E.\n\nZHIYING (GIN) JIANG\, PHD CANDIDATE\n_David R. Cheriton School of Co
 mputer Science_\n\nSUPERVISOR: Professor Jimmy Lin\n\nIn this thesis\, we 
 aim at improving interpretability and\ngeneralizability through restrictin
 g representations. We choose to\napproach interpretability by focusing on 
 attribution analysis to\nunderstand which features contribute to predictio
 n on BERT\, and to\napproach generalizability by focusing on effective met
 hods in low-data\nregime.\n 
DTSTAMP:20250525T150007Z
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