4 papers
Hard-Negative Sampling for Contrastive Learning: Optimal Representation Geometry and Neural- vs Dimensional-Collapse
Ruijie Jiang, Thuan Nguyen, Shuchin Aeron +1
For a widely-studied data model and general loss and sample-hardening functions we prove that the losses of Supervised Contrastive Learning (SCL), Hard-SCL (HSCL), and Unsupervised…
A Lesion-aware Edge-based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia
Zijian Chen, Maria Varkanitsa, Prakash Ishwar +4
We propose a lesion-aware graph neural network (LEGNet) to predict language ability from resting-state fMRI (rs-fMRI) connectivity in patients with post-stroke aphasia. Our model i…
Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage
Isidora Chara Tourni, Lei Guo, Hengchang Hu +9
News media structure their reporting of events or issues using certain perspectives. When describing an incident involving gun violence, for example, some journalists may focus on…
Supervised Contrastive Learning with Hard Negative Samples
Ruijie Jiang, Thuan Nguyen, Prakash Ishwar +1
Through minimization of an appropriate loss function such as the InfoNCE loss, contrastive learning (CL) learns a useful representation function by pulling positive samples close t…