research
∙
06/01/2022
ILMART: Interpretable Ranking with Constrained LambdaMART
Interpretable Learning to Rank (LtR) is an emerging field within the res...
share
research
∙
12/29/2021
EiFFFeL: Enforcing Fairness in Forests by Flipping Leaves
Nowadays Machine Learning (ML) techniques are extensively adopted in man...
research
∙
12/05/2021
Beyond Robustness: Resilience Verification of Tree-Based Classifiers
In this paper we criticize the robustness measure traditionally employed...
research
∙
05/06/2021
Learning Early Exit Strategies for Additive Ranking Ensembles
Modern search engine ranking pipelines are commonly based on large machi...
research
∙
04/30/2020
Query-level Early Exit for Additive Learning-to-Rank Ensembles
Search engine ranking pipelines are commonly based on large ensembles of...
research
∙
04/07/2020
Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios
Machine learning algorithms, however effective, are known to be vulnerab...
research
∙
07/02/2019