In this paper we propose a new framework, named CLEaVER, for optimizing machine-learned ranking models based on ensembles of regression trees. The goal is to ...
Jul 17, 2016 · The goal is to improve efficiency at document scoring time without affecting quality. Since the cost of an ensemble is linear in its size, ...
Jul 17, 2016 · Post-Learning Optimization of Tree Ensembles for Efficient Ranking ... We present a framework, named CLEaVER, for the optimization of tree ...
In this paper we propose a new framework, named CLEaVER, for optimizing machine-learned ranking models based on ensembles of regression trees. The goal is to ...
Mar 31, 2016 · In this paper we propose a new framework, named CLEaVER, for optimizing machine-learned ranking models based on ensembles of regression trees.
Jan 3, 2022 · Bibliographic details on Post-Learning Optimization of Tree Ensembles for Efficient Ranking.
We summarize the results of a comprehensive evaluation showing that CLEaVER is able to prune up to 80% of the trees and provides an efficiency speed-up up to ...
Alternating Optimization of Decision Trees with Application to Learning Sparse Oblique Trees ... Post-Learning Optimization of Tree Ensembles for Efficient ...
Oct 9, 2019 · Here, we show that our approach can optimize large-scale tree ensemble models with thousands of independent variables to full or near optimality ...
May 30, 2017 · In this paper, we study the problem of tree ensemble optimization: given a tree ensemble that predicts some dependent variable using controllable independent ...
Missing: Post- Ranking.