The section on distributed multi-task learning provides an overview of its concepts, benefits, and challenges. The paper then discusses some of the popular algorithms used in distributed multi-task ...

In many real-world applications, data are distributed across different geographical regions, and may come from different distributions which result in multiple learning tasks. In such cases, ...

GenSen is a technique to learn general purpose, fixed-length representations of sentences via multi-task training. These representations are useful for transfer and low-resource learning. For details ...

This is the implementation of the paper Multi-Task Learning Using Dynamic Weights of Tasks for Face Recognition withFacial Expression published on the ICCV workshop 2019, which simultaneously perform ...

This document serves as user manual for HydraGNN, a scalable graph neural network (GNN) architecture that allows for a simultaneous prediction of multiple target properties using multi-task learning ...