What is med-DECILE

Reduce end to end training time from days to hours and hours to minutes using coresets and data selection. CORDS implements a number of state of the art data subset selection algorithms and coreset algorithms. Some of the algorithms currently implemented with CORDS include: GLISTER, GradMatchOMP, GradMatchFixed, CRAIG, SubmodularSelection, RandomSelection etc

DISTIL is a library that features many state-of-the-art active learning algorithms. Implemented in PyTorch, it gives fast and efficient implementations of these active learning algorithms. It allows users to modularly insert active learning selection into their pre-existing training loops with minimal change. Most importantly, it features promising results in achieving high model performance with less amount of labeled data. If you are looking to cut down on labeling costs, DISTIL should be your go-to for getting the most out of your data.

Summarize massive datasets using submodular optimization

SPEAR is a python library that reduce data labeling efforts using data programming. It implements several recent approaches such as Snorkel, ImplyLoss, Learning to reweight, etc. In addition to data labeling, it integrates semi-supervised approaches for training and inference.

Targeted subset selection