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.
Study proposes a clustering and logistic regression algorithm for PU classification under Non-SCAR.
Generic scarring occurs along stable minimal hypersurfaces in 3-7 dimensional manifolds.
Minimal hypersurfaces scarring along a fixed one in certain manifolds.
Test verifies if data meets SCAR assumption for PU learning.
Study on random surfaces in hyperbolic 3-manifolds, focusing on geometric and topological properties.
New model tackles PU data with better accuracy.
Machine learning (ML) training algorithms often possess an inherent self-correcting behavior due to their iterative-convergent nature. Recent systems exploit this property to achieve adaptability and efficiency in unreliable computing environments by relaxing the consistency of execution and allowing calculation errors…
This work improves LePU by modeling the annotation process more realistically.
Paper proposes LC-Checkpoint for efficient deep learning model checkpoints.
Improved classifier for PU data using logistic regression.
Proposes methods to estimate posterior probability and propensity score functions without assuming constant propensity score.