Learning multivariate Gaussians with imperfect advice

We revisit the problem of distribution learning within the framework of learning-augmented algorithms. In this setting, we explore the scenario where a probability distribution is provided as potentially inaccurate advice on the true, unknown distribution. Our objective is to develop learning algori...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	arXiv.org 2024-11
Hauptverfasser:	Bhattacharyya, Arnab, Choo, Davin, Philips, George John, Gouleakis, Themis
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Lower bounds Machine learning Multivariate analysis Normal distribution Polynomials Statistical analysis
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!