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.
Causal forests use honesty to reduce overfitting, but it can also reduce accuracy, especially with large datasets.
Game theory models incentivizes honesty in collaborative learning among competitors.
Due to their accuracies, methods based on ensembles of regression trees are a popular approach for making predictions. Some common examples include Bayesian additive regression trees, boosting and random forests. This paper focuses on honest random forests, which add honesty to the original form of random forests and a…
Causal trees struggle with accuracy in estimating treatment effects.
SDRF estimates complex survey designs for conditional distributions.
The mass, or binding energy, is the basis property of the atomic nucleus. It determines its stability, and reaction and decay rates. Quantifying the nuclear binding is important for understanding the origin of elements in the universe. The astrophysical processes responsible for the nucleosynthesis in stars often take …
The cost of belief changes with precision and is a hyperbolic geometry.