14 citations · 25 across the 7 of their papers we have counts for
7 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…
Systematic comparison of semi-supervised and self-supervised learning for medical image classification
Zhe Huang, Ruijie Jiang, Shuchin Aeron +1
In typical medical image classification problems, labeled data is scarce while unlabeled data is more available. Semi-supervised learning and self-supervised learning are two diffe…
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…
Measure Estimation in the Barycentric Coding Model
Matthew Werenski, Ruijie Jiang, Abiy Tasissa +2
This paper considers the problem of measure estimation under the barycentric coding model (BCM), in which an unknown measure is assumed to belong to the set of Wasserstein-2 baryce…
Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning
Ruijie Jiang, Prakash Ishwar, Shuchin Aeron
We study the problem of designing hard negative sampling distributions for unsupervised contrastive representation learning. We propose and analyze a novel min-max framework that s…
Interpretable contrastive word mover's embedding
Ruijie Jiang, Julia Gouvea, Eric Miller +2
This paper shows that a popular approach to the supervised embedding of documents for classification, namely, contrastive Word Mover's Embedding, can be significantly enhanced by a…
Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space
Ruijie Jiang, Julia Gouvea, David Hammer +2
Qualitative analysis of verbal data is of central importance in the learning sciences. It is labor-intensive and time-consuming, however, which limits the amount of data researcher…