no code implementations • 2 Feb 2024 • Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi, Wei Chen
We study a general clustering setting in which we have $n$ elements to be clustered, and we aim to perform as few queries as possible to an oracle that returns a noisy sample of the similarity between two elements.
no code implementations • 29 Jan 2024 • Andrew Bell, Joao Fonseca, Carlo Abrate, Francesco Bonchi, Julia Stoyanovich
Building upon an agent-based framework for simulating recourse, this paper demonstrates how much effort is needed to overcome disparities in initial circumstances.
1 code implementation • 27 Nov 2023 • Gabriele D'Acunto, Paolo Di Lorenzo, Francesco Bonchi, Stefania Sardellitti, Sergio Barbarossa
Despite the large research effort devoted to learning dependencies between time series, the state of the art still faces a major limitation: existing methods learn partial correlations but fail to discriminate across distinct frequency bands.
1 code implementation • 31 Oct 2023 • Gabriele D'Acunto, Francesco Bonchi, Gianmarco De Francisci Morales, Giovanni Petri
The bulk of the research effort on brain connectivity revolves around statistical associations among brain regions, which do not directly relate to the causal mechanisms governing brain dynamics.
no code implementations • 13 Sep 2023 • Joao Fonseca, Andrew Bell, Carlo Abrate, Francesco Bonchi, Julia Stoyanovich
The bulk of the literature on algorithmic recourse to-date focuses primarily on how to provide recourse to a single individual, overlooking a critical element: the effects of a continuously changing context.
1 code implementation • 28 Aug 2023 • Federico Cinus, Aristides Gionis, Francesco Bonchi
Social media have great potential for enabling public discourse on important societal issues.
1 code implementation • 27 Jul 2023 • Carlo Abrate, Giulia Preti, Francesco Bonchi
Counterfactual examples have emerged as an effective approach to produce simple and understandable post-hoc explanations.
no code implementations • 7 Jun 2023 • Francesco Bonchi, Claudio Gentile, Francesco Paolo Nerini, André Panisson, Fabio Vitale
We present a new effective and scalable framework for training GNNs in node classification tasks, based on the effective resistance, a powerful tool solidly rooted in graph theory.
no code implementations • 25 Mar 2023 • Tommaso Lanciano, Atsushi Miyauchi, Adriano Fazzone, Francesco Bonchi
This survey provides a deep overview of the fundamental results and an exhaustive coverage of the many variants proposed in the literature, with a special attention on the most recent results.
1 code implementation • 2 Nov 2022 • Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang
Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications -- including data summarization, influence maximization, and recommendation.
no code implementations • 31 Aug 2022 • Gabriele D'Acunto, Gianmarco De Francisci Morales, Paolo Bajardi, Francesco Bonchi
Our model allows sampling an MN-DAG according to user-specified priors on the time-dependence and multiscale properties of the causal graph.
1 code implementation • 9 Aug 2022 • Marco Minici, Federico Cinus, Corrado Monti, Francesco Bonchi, Giuseppe Manco
Experiments on synthetic data show that our algorithm is able to correctly reconstruct ground-truth latent communities with their degree of echo-chamber behavior and opinion polarity.
no code implementations • 10 May 2022 • Corrado Monti, Marco Pangallo, Gianmarco De Francisci Morales, Francesco Bonchi
In this paper, we propose a protocol to learn the latent micro-variables of an ABM from data.
no code implementations • 17 Feb 2022 • Alan Perotti, Paolo Bajardi, Francesco Bonchi, André Panisson
Decoupling the feature space (edges) from a desired high-level explanation language (such as motifs) is thus a major challenge towards developing actionable explanations for graph classification tasks.
1 code implementation • 1 Feb 2022 • Francesco Fabbri, Yanhao Wang, Francesco Bonchi, Carlos Castillo, Michael Mathioudakis
Hence, we define the problem of reducing the prevalence of radicalization pathways by selecting a small number of edges to "rewire", so to minimize the maximum of segregation scores among all radicalized nodes, while maintaining the relevance of the recommendations.
no code implementations • 9 Nov 2021 • Gabriele D'Acunto, Paolo Bajardi, Francesco Bonchi, Gianmarco De Francisci Morales
They link the evolution of the causal structure of equity risk factors with market volatility and a worsening macroeconomic environment, and show that, in times of financial crisis, exposure to different factors boils down to exposure to the market risk factor.
1 code implementation • 28 Sep 2021 • Corrado Monti, Giuseppe Manco, Cigdem Aslay, Francesco Bonchi
Modeling information cascades in a social network through the lenses of the ideological leaning of its users can help understanding phenomena such as misinformation propagation and confirmation bias, and devising techniques for mitigating their toxic effects.
1 code implementation • 16 Jun 2021 • Carlo Abrate, Francesco Bonchi
In this paper we propose \emph{counterfactual graphs} as a way to produce local post-hoc explanations of any black-box graph classifier.
no code implementations • 16 Jun 2021 • David Garcia-Soriano, Francesco Bonchi
Our proposal is rooted in the distributional maxmin fairness theory, which uses randomization to maximize the expected satisfaction of the worst-off individuals.
1 code implementation • 2 Jun 2020 • Corrado Monti, Gianmarco De Francisci Morales, Francesco Bonchi
In this work we propose an inference mechanism for fitting a generative, agent-like model of opinion dynamics to real-world social traces.
no code implementations • 26 Feb 2020 • David García-Soriano, Konstantin Kutzkov, Francesco Bonchi, Charalampos Tsourakakis
Up to constant factors, our algorithm yields a provably optimal trade-off between the number of queries $Q$ and the worst-case error attained, even for adaptive algorithms.
no code implementations • 6 Aug 2018 • Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti
Experiments on synthetic data show that our method is able to retrieve the genuine causal arcs w. r. t.
2 code implementations • 20 Jun 2017 • Meike Zehlike, Francesco Bonchi, Carlos Castillo, Sara Hajian, Mohamed Megahed, Ricardo Baeza-Yates
In this work, we define and solve the Fair Top-k Ranking problem, in which we want to determine a subset of k candidates from a large pool of n >> k candidates, maximizing utility (i. e., select the "best" candidates) subject to group fairness criteria.
no code implementations • 2 Oct 2015 • Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
Discrimination discovery from data is an important task aiming at identifying patterns of illegal and unethical discriminatory activities against protected-by-law groups, e. g., ethnic minorities.
no code implementations • 30 Sep 2011 • Amit Goyal, Francesco Bonchi, Laks. V. S. Lakshmanan
In particular, we introduce a new model, which we call credit distribution, that directly leverages available propagation traces to learn how influence flows in the network and uses this to estimate expected influence spread.
Databases