2 papers
cs.LG2022
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
Charline Le Lan, Joshua Greaves, Jesse Farebrother +4
Many machine learning problems encode their data as a matrix with a possibly very large number of rows and columns. In several applications like neuroscience, image compression or…
cs.CV2020
Multi-path Neural Networks for On-device Multi-domain Visual Classification
Qifei Wang, Junjie Ke, Joshua Greaves +9
Learning multiple domains/tasks with a single model is important for improving data efficiency and lowering inference cost for numerous vision tasks, especially on resource-constra…