scispace - formally typeset
A

Anna Monreale

Researcher at University of Pisa

Publications -  110
Citations -  6369

Anna Monreale is an academic researcher from University of Pisa. The author has contributed to research in topics: Computer science & Information privacy. The author has an hindex of 24, co-authored 95 publications receiving 4458 citations. Previous affiliations of Anna Monreale include National Research Council & Istituto di Scienza e Tecnologie dell'Informazione.

Papers
More filters
Journal ArticleDOI

A Survey of Methods for Explaining Black Box Models

TL;DR: In this paper, the authors provide a classification of the main problems addressed in the literature with respect to the notion of explanation and the type of black box decision support systems, given a problem definition, a black box type, and a desired explanation, this survey should help the researcher to find the proposals more useful for his own work.
Proceedings ArticleDOI

WhereNext: a location predictor on trajectory pattern mining

TL;DR: This paper proposes WhereNext, which is a method aimed at predicting with a certain level of accuracy the next location of a moving object, which uses previously extracted movement patterns named Trajectory Patterns, which are a concise representation of behaviors of moving objects as sequences of regions frequently visited with a typical travel time.
Posted Content

Local Rule-Based Explanations of Black Box Decision Systems.

TL;DR: This paper proposes LORE, an agnostic method able to provide interpretable and faithful explanations for black box outcome explanation, and shows that LORE outperforms existing methods and baselines both in the quality of explanations and in the accuracy in mimicking the black box.
Posted Content

A Survey Of Methods For Explaining Black Box Models

TL;DR: In this paper, the authors provide a classification of the main problems addressed in the literature with respect to the notion of explanation and the type of black box decision support system given a problem definition, a black box type, and a desired explanation.
Journal ArticleDOI

Factual and Counterfactual Explanations for Black Box Decision Making

TL;DR: A local rule-based explanation method, providing faithful explanations of the decision made by a black box classifier on a specific instance, outperforms existing approaches in terms of the quality of the explanations and of the accuracy in mimicking the black box.