3 papers
cs.CL2026
Unsupervised Text Segmentation via Kernel Change-Point Detection on Sentence Embeddings
Mumin Jia, Jairo Diaz-Rodriguez
Unsupervised text segmentation is crucial because boundary labels are expensive, subjective, and often fail to transfer across domains and granularity choices. We propose Embed-KCP…
cs.CV2025
Structured Output Regularization: a framework for few-shot transfer learning
Nicolas Ewen, Jairo Diaz-Rodriguez, Kelly Ramsay
Traditional transfer learning typically reuses large pre-trained networks by freezing some of their weights and adding task-specific layers. While this approach is computationally…
cs.LG2025
Consistent Kernel Change-Point Detection under m-Dependence for Text Segmentation
Jairo Diaz-Rodriguez, Mumin Jia
Kernel change-point detection (KCPD) has become a widely used tool for identifying structural changes in complex data. While existing theory establishes consistency under independe…