A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper reproduces a kernel-based scan B-statistic for online change-point detection.
Detecting the emergence of an abrupt change-point is a classic problem in statistics and machine learning. Kernel-based nonparametric statistics have been used for this task which enjoy fewer assumptions on the distributions than the parametric approach and can handle high-dimensional data. In this paper we focus on th…
Paper presents deep learning and ML for automated student performance estimation.
Efficient online kernel CUSUM detects changes quickly and accurately.