3 papers
cs.LG2026
A Stationary-Distribution Theory for Triplet-Based Plateau Search in Random Forest Ensemble-Size Selection
Andrey A. Dukhovny, Andrey M. Lange
The number of trees is a central computational parameter in Random Forests: increasing it reduces finite-ensemble variability but increases training and prediction cost. Plateau-ba…
cs.LG2026
How Many Trees in a Random Forest? A Revisited Approach with Plateau Search and Optuna Integration
Vadim Porvatov, Andrey Dukhovny, Andrey Lange
Hyperparameter optimization (HPO) for Random Forest faces a specific difficulty in tuning the number of trees: the predictive score typically improves monotonically with ensemble s…
cs.LG2024
MLEM: Generative and Contrastive Learning as Distinct Modalities for Event Sequences
Viktor Moskvoretskii, Dmitry Osin, Egor Shvetsov +5
This study explores the application of self-supervised learning techniques for event sequences. It is a key modality in various applications such as banking, e-commerce, and health…