1 citations · 1 across the 5 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
PINE: Pruning Boosted Tree Ensembles with Conformal In-Distribution Prediction Equivalence
Haruki Yajima, Yusuke Matsui
Tree ensembles are machine learning models with strong predictive performance and interpretability, and remain widely used for tabular data. Standard pruning methods for tree ensem…
cs.LG2026
Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functions
Atsuki Sato, Martin Aumüller, Yusuke Matsui
Learned indexes are a class of index data structures that enable fast search by approximating the cumulative distribution function (CDF) using machine learning models (Kraska et al…
cs.LG2025
Optimized Learned Count-Min Sketch
Kyosuke Nishishita, Atsuki Sato, Yusuke Matsui
Count-Min Sketch (CMS) is a memory-efficient data structure for estimating the frequency of elements in a multiset. Learned Count-Min Sketch (LCMS) enhances CMS with a machine lear…