Sharing to learn and learning to share--Fitting together Meta-Learning, Multi-Task Learning, and Transfer Learning: A meta review
R Upadhyay, R Phlypo, R Saini, M Liwicki - ar** for cold-start diagnosis prediction in healthcare data
Cold-start diagnosis prediction is a challenging task for AI in healthcare, where often only a
few visits per patient and a few observations per disease can be exploited. Although meta …
few visits per patient and a few observations per disease can be exploited. Although meta …
EDVAE: Disentangled latent factors models in counterfactual reasoning for individual treatment effects estimation
Estimating individual treatment effect (ITE) from observational data is a crucial but
challenging task. Disentangled representations have been used to separate proxy variables …
challenging task. Disentangled representations have been used to separate proxy variables …
Learning to customize model structures for few-shot dialogue generation tasks
Training the generative models with minimal corpus is one of the critical challenges for
building open-domain dialogue systems. Existing methods tend to use the meta-learning …
building open-domain dialogue systems. Existing methods tend to use the meta-learning …
Entity aware modelling: A survey
Personalized prediction of responses for individual entities caused by external drivers is vital
across many disciplines. Recent machine learning (ML) advances have led to new state-of …
across many disciplines. Recent machine learning (ML) advances have led to new state-of …
A comprehensive evaluation of multi-task learning and multi-task pre-training on ehr time-series data
Multi-task learning (MTL) is a machine learning technique aiming to improve model
performance by leveraging information across many tasks. It has been used extensively on …
performance by leveraging information across many tasks. It has been used extensively on …
Explainable multi-task learning approach for skin lesion classification
K Patel, N Mehta, S Easwaran, R Walambe… - IoT Sensors, ML, AI and …, 2024 - Springer
The early diagnosis of skin cancer has significantly improved with the use of computer-aided
techniques and deep learning (DL) models. However, existing methods often struggle with …
techniques and deep learning (DL) models. However, existing methods often struggle with …
[HTML][HTML] A gradient boosting tree model for multi-department venous thromboembolism risk assessment with imbalanced data
Venous thromboembolism (VTE) is the world's third most common cause of vascular
mortality and a serious complication from multiple departments. Risk assessment of VTE …
mortality and a serious complication from multiple departments. Risk assessment of VTE …
TGGS network: A multi-task learning network for gradient-guided knowledge sharing
Y Huang, X Han, M Chen, Z Pan - Knowledge-Based Systems, 2024 - Elsevier
Multi-task learning (MTL) has been widely used in various fields, such as time series data
prediction and image classification. Most existing deep MTL methods achieve joint learning …
prediction and image classification. Most existing deep MTL methods achieve joint learning …