arXiv stat.ML
· Papers
Boundary Density Likelihood for Direct Event-Time Supervision
arXiv:2408.12792v2 Announce Type: replace-cross Abstract: Event detection turns long recordings into a sparse set of ranked timestamps. Yet many sequence models are trained for samplewise segmentation and only convert predicted states into events after training. We ask whether training directly for the evaluated output