6 citations · 6 across the 4 of their papers we have counts for
5 papers
All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training
Islam Nassar, Samitha Herath, Ehsan Abbasnejad +2
Pseudo-labeling is a key component in semi-supervised learning (SSL). It relies on iteratively using the model to generate artificial labels for the unlabeled data to train against…
Topic Modelling Meets Deep Neural Networks: A Survey
He Zhao, Dinh Phung, Viet Huynh +3
Topic modelling has been a successful technique for text analysis for almost twenty years. When topic modelling met deep neural networks, there emerged a new and increasingly popul…
Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction
Bhagya Hettige, Weiqing Wang, Yuan-Fang Li +2
Predicting (1) when the next hospital admission occurs and (2) what will happen in the next admission about a patient by mining electronic health record (EHR) data can provide gran…
Discriminative, Generative and Self-Supervised Approaches for Target-Agnostic Learning
Yuan Jin, Wray Buntine, Francois Petitjean +1
Supervised learning, characterized by both discriminative and generative learning, seeks to predict the values of single (or sometimes multiple) predefined target attributes based…
Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation
Fahimeh Saleh, Wray Buntine, Gholamreza Haffari
Scarcity of parallel sentence-pairs poses a significant hurdle for training high-quality Neural Machine Translation (NMT) models in bilingually low-resource scenarios. A standard a…