1 citations · 1 across the 4 of their papers we have counts for
4 papers
Training Over a Distribution of Hyperparameters for Enhanced Performance and Adaptability on Imbalanced Classification
Kelsey Lieberman, Swarna Kamlam Ravindran, Shuai Yuan +1
Although binary classification is a well-studied problem, training reliable classifiers under severe class imbalance remains a challenge. Recent techniques mitigate the ill effects…
Optimizing for ROC Curves on Class-Imbalanced Data by Training over a Family of Loss Functions
Kelsey Lieberman, Shuai Yuan, Swarna Kamlam Ravindran +1
Although binary classification is a well-studied problem in computer vision, training reliable classifiers under severe class imbalance remains a challenging problem. Recent work h…
RandMSAugment: A Mixed-Sample Augmentation for Limited-Data Scenarios
Swarna Kamlam Ravindran, Carlo Tomasi
The high costs of annotating large datasets suggests a need for effectively training CNNs with limited data, and data augmentation is a promising direction. We study foundational a…
UFD-PRiME: Unsupervised Joint Learning of Optical Flow and Stereo Depth through Pixel-Level Rigid Motion Estimation
Shuai Yuan, Carlo Tomasi
Both optical flow and stereo disparities are image matches and can therefore benefit from joint training. Depth and 3D motion provide geometric rather than photometric information…