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 compares feature selection methods using GCM and LOCO, showing GCM methods generally outperform LOCO.
TabPFN models achieve state-of-the-art performance on tabular data tasks.
A new efficient test addresses limitations of knockoffs for conditional independence testing.
The paper derives theoretical foundations for two common machine learning variable importance measures.
iLOCO measures feature interactions without assumptions, providing statistical inference.
New method disentangles high-order effects in feature importance.
We develop a general framework for distribution-free predictive inference in regression, using conformal inference. The proposed methodology allows for the construction of a prediction band for the response variable using any estimator of the regression function. The resulting prediction band preserves the consistency …
A new method for feature importance inference without data splitting.
Cluster LOCO: A model-agnostic feature importance score for interpreting cluster outputs