research
∙
06/16/2023
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning
Labeled data are critical to modern machine learning applications, but o...
share
research
∙
06/15/2023
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
Modern machine learning models deployed in the wild can encounter both c...
research
∙
07/07/2022
One for All: Simultaneous Metric and Preference Learning over Multiple Users
This paper investigates simultaneous preference and metric learning from...
research
∙
02/28/2021
Feedback Coding for Active Learning
The iterative selection of examples for labeling in active machine learn...
research
∙
06/24/2020
Generative causal explanations of black-box classifiers
We develop a method for generating causal post-hoc explanations of black...
research
∙
10/09/2019
