The Spectral Condition Number Plot for Regularization Parameter Determination
원문 초록
Many modern statistical applications ask for the estimation of a covariance (or precision) matrix in settings where the number of variables is larger than the number of observations. There exists a broad class of ridge-type estimators that employs regularization to cope with the subsequent singularity of the sample covariance matrix. These estimators depend on a penalty parameter and choosing its value can be hard, in terms of being computationally unfeasible or tenable only for a restricted set of ridge-type estimators. Here we introduce a simple graphical tool, the spectral condition number plot, for informed heuristic penalty parameter selection. The proposed tool is computationally friendly and can be employed for the full class of ridge-type covariance (precision) estimators.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis
Revisiting Deep Learning for Variable Type Recovery
Mask Detection and Classification in Thermal Face Images
TypeT5: Seq2seq Type Inference using Static Analysis
Safe-DS: A Domain Specific Language to Make Data Science Safe
Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text
토론
이 논문과 연결된 포럼 글이 아직 없습니다.