3 papers
cs.CV2026
Learning to Segment using Summary Statistics and Weak Supervision
Omkar Kulkarni, Edward Raff, Tim Oates
Medical experts often manually segment images to obtain diagnostic statistics and discard the resulting annotations. We aim to train segmentation models to alleviate this burden, b…
cs.LG2025
A Vector Symbolic Approach to Multiple Instance Learning
Ehsan Ahmed Dhrubo, Mohammad Mahmudul Alam, Edward Raff +2
Multiple Instance Learning (MIL) tasks impose a strict logical constraint: a bag is labeled positive if and only if at least one instance within it is positive. While this iff cons…
cs.CV2025
DeBUGCN -- Detecting Backdoors in CNNs Using Graph Convolutional Networks
Akash Vartak, Khondoker Murad Hossain, Tim Oates
Deep neural networks (DNNs) are becoming commonplace in critical applications, making their susceptibility to backdoor (trojan) attacks a significant problem. In this paper, we int…