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05/15/2023
Efficient and Effective Tree-based and Neural Learning to Rank
This monograph takes a step towards promoting the study of efficiency in...
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05/15/2023
Fast Inference of Tree Ensembles on ARM Devices
With the ongoing integration of Machine Learning models into everyday li...
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12/29/2022
A Theoretical Framework for AI Models Explainability
Explainability is a vibrant research topic in the artificial intelligenc...
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09/27/2022
Explainable Global Fairness Verification of Tree-Based Classifiers
We present a new approach to the global fairness verification of tree-ba...
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06/01/2022
ILMART: Interpretable Ranking with Constrained LambdaMART
Interpretable Learning to Rank (LtR) is an emerging field within the res...
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12/29/2021
EiFFFeL: Enforcing Fairness in Forests by Flipping Leaves
Nowadays Machine Learning (ML) techniques are extensively adopted in man...
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12/05/2021
Beyond Robustness: Resilience Verification of Tree-Based Classifiers
In this paper we criticize the robustness measure traditionally employed...
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05/06/2021
Learning Early Exit Strategies for Additive Ranking Ensembles
Modern search engine ranking pipelines are commonly based on large machi...
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07/06/2020
Certifying Decision Trees Against Evasion Attacks by Program Analysis
Machine learning has proved invaluable for a range of different tasks, y...
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04/30/2020
Query-level Early Exit for Additive Learning-to-Rank Ensembles
Search engine ranking pipelines are commonly based on large ensembles of...
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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...
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07/02/2019
Treant: Training Evasion-Aware Decision Trees
Despite its success and popularity, machine learning is now recognized a...
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11/06/2018