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Found 7 papers, 5 papers with code
On neural and dimensional collapse in supervised and unsupervised contrastive learning with hard negative sampling
For a widely-studied data model and general loss and sample-hardening functions we prove that the Supervised Contrastive Learning (SCL), Hard-SCL (HSCL), and Unsupervised Contrastive Learning (UCL) risks are minimized by representations that exhibit Neural Collapse (NC), i. e., the class means form an Equianglular Tight Frame (ETF) and data from the same class are mapped to the same representation.
Systematic comparison of semi-supervised and self-supervised learning for medical image classification
Yet past benchmarks do not focus on medical tasks and rarely compare self- and semi- methods together on an equal footing.
Supervised Contrastive Learning with Hard Negative Samples
In this paper, motivated by the effectiveness of hard-negative sampling strategies in H-UCL and the usefulness of label information in SCL, we propose a contrastive learning framework called hard-negative supervised contrastive learning (H-SCL).
Measure Estimation in the Barycentric Coding Model
Our first main result leverages the Riemannian geometry of Wasserstein-2 space to provide a procedure for recovering the barycentric coordinates as the solution to a quadratic optimization problem assuming access to the true reference measures.
Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning
We study the problem of designing hard negative sampling distributions for unsupervised contrastive representation learning.
Interpretable contrastive word mover's embedding
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 adding interpretability.
Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space
This work is a step towards building a statistical machine learning (ML) method for achieving an automated support for qualitative analyses of students' writing, here specifically in score laboratory reports in introductory biology for sophistication of argumentation and reasoning.
