5 citations · 17 across the 23 of their papers we have counts for
3 papers · 1 filter
Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
Shyam Nuggehalli, Jifan Zhang, Lalit Jain +1
Class imbalance severely impacts machine learning performance on minority classes in real-world applications. While various solutions exist, active learning offers a fundamental fi…
LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning
Jifan Zhang, Yifang Chen, Gregory Canal +8
Labeled data are critical to modern machine learning applications, but obtaining labels can be expensive. To mitigate this cost, machine learning methods, such as transfer learning…
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Jifan Zhang, Shuai Shao, Saurabh Verma +1
Label efficiency has become an increasingly important objective in deep learning applications. Active learning aims to reduce the number of labeled examples needed to train deep ne…