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Fabio Massimo Zennaro
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2020 – today
- 2024
- [j7]Åvald Åslaugson Sommervoll
, László Erdodi, Fabio Massimo Zennaro:
Simulating all archetypes of SQL injection vulnerability exploitation using reinforcement learning agents. Int. J. Inf. Sec. 23(1): 225-246 (2024) - [c9]Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas:
Causal Optimal Transport of Abstractions. CLeaR 2024: 462-498 - [i20]Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael J. Wooldridge, Theodoros Damoulas:
Causally Abstracted Multi-armed Bandits. CoRR abs/2404.17493 (2024) - 2023
- [j6]Fabio Massimo Zennaro
, László Erdodi:
Modelling penetration testing with reinforcement learning using capture-the-flag challenges: Trade-offs between model-free learning and a priori knowledge. IET Inf. Secur. 17(3): 441-457 (2023) - [c8]Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas:
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CLeaR 2023: 88-121 - [c7]Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas:
Quantifying Consistency and Information Loss for Causal Abstraction Learning. IJCAI 2023: 5750-5757 - [i19]Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas:
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CoRR abs/2301.05893 (2023) - [i18]Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas:
Quantifying Consistency and Information Loss for Causal Abstraction Learning. CoRR abs/2305.04357 (2023) - [i17]Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas:
Causal Optimal Transport of Abstractions. CoRR abs/2312.08107 (2023) - [i16]Joel Dyer
, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Anisoara Calinescu, Theodoros Damoulas, Michael J. Wooldridge:
Interventionally Consistent Surrogates for Agent-based Simulators. CoRR abs/2312.11158 (2023) - 2022
- [j5]Anis Yazidi
, Magdalena Ivanovska, Fabio Massimo Zennaro
, Pedro G. Lind
, Enrique Herrera-Viedma:
A new decision making model based on Rank Centrality for GDM with fuzzy preference relations. Eur. J. Oper. Res. 297(3): 1030-1041 (2022) - [j4]László Erdodi
, Fabio Massimo Zennaro
:
The Agent Web Model: modeling web hacking for reinforcement learning. Int. J. Inf. Sec. 21(2): 293-309 (2022) - [i15]Fabio Massimo Zennaro:
Abstraction between Structural Causal Models: A Review of Definitions and Properties. CoRR abs/2207.08603 (2022) - [i14]Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas:
Towards Computing an Optimal Abstraction for Structural Causal Models. CoRR abs/2208.00894 (2022) - 2021
- [j3]László Erdödi, Åvald Åslaugson Sommervoll
, Fabio Massimo Zennaro
:
Simulating SQL injection vulnerability exploitation using Q-learning reinforcement learning agents. J. Inf. Secur. Appl. 61: 102903 (2021) - [c6]Manuel Del Verme, Åvald Åslaugson Sommervoll, László Erdödi, Simone Totaro, Fabio Massimo Zennaro
:
SQL Injections and Reinforcement Learning: An Empirical Evaluation of the Role of Action Structure. NordSec 2021: 95-113 - [i13]Laszlo Erdodi, Åvald Åslaugson Sommervoll, Fabio Massimo Zennaro:
Simulating SQL Injection Vulnerability Exploitation Using Q-Learning Reinforcement Learning Agents. CoRR abs/2101.03118 (2021) - 2020
- [c5]Alexander Egiazarov, Fabio Massimo Zennaro
, Vasileios Mavroeidis:
Firearm Detection via Convolutional Neural Networks: Comparing a Semantic Segmentation Model Against End-to-End Solutions. IEEE BigData 2020: 1796-1804 - [c4]Fabio Massimo Zennaro
:
A Left Realist Critique of the Political Value of Adopting Machine Learning Systems in Criminal Justice. PKDD/ECML Workshops 2020: 92-107 - [i12]Alexander Egiazarov, Vasileios Mavroeidis, Fabio Massimo Zennaro, Kamer Vishi:
Firearm Detection and Segmentation Using an Ensemble of Semantic Neural Networks. CoRR abs/2003.00805 (2020) - [i11]Fabio Massimo Zennaro, Laszlo Erdodi:
Modeling Penetration Testing with Reinforcement Learning Using Capture-the-Flag Challenges and Tabular Q-Learning. CoRR abs/2005.12632 (2020) - [i10]Fabio Massimo Zennaro, Audun Jøsang:
Using Subjective Logic to Estimate Uncertainty in Multi-Armed Bandit Problems. CoRR abs/2008.07386 (2020) - [i9]Laszlo Erdodi, Fabio Massimo Zennaro:
The Agent Web Model - Modelling web hacking for reinforcement learning. CoRR abs/2009.11274 (2020) - [i8]Alexander Egiazarov, Fabio Massimo Zennaro, Vasileios Mavroeidis:
Firearm Detection via Convolutional Neural Networks: Comparing a Semantic Segmentation Model Against End-to-End Solutions. CoRR abs/2012.09662 (2020) - [i7]William Arild Dahl, Laszlo Erdodi, Fabio Massimo Zennaro:
Stack-based Buffer Overflow Detection using Recurrent Neural Networks. CoRR abs/2012.15116 (2020)
2010 – 2019
- 2019
- [j2]Fabio Massimo Zennaro
, Magdalena Ivanovska
, Audun Jøsang
:
An empirical evaluation of the approximation of subjective logic operators using Monte Carlo simulations. Int. J. Approx. Reason. 111: 56-77 (2019) - [c3]Alexander Egiazarov, Vasileios Mavroeidis, Fabio Massimo Zennaro
, Kamer Vishi
:
Firearm Detection and Segmentation Using an Ensemble of Semantic Neural Networks. EISIC 2019: 70-77 - [c2]Fabio Massimo Zennaro
:
Analyzing and Storing Network Intrusion Detection Data Using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings. PKDD/ECML Workshops (2) 2019: 208-222 - [i6]Fabio Massimo Zennaro:
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings. CoRR abs/1906.08528 (2019) - [i5]Fabio Massimo Zennaro, Ke Chen
:
Towards Further Understanding of Sparse Filtering via Information Bottleneck. CoRR abs/1910.08964 (2019) - 2018
- [j1]Fabio Massimo Zennaro
, Ke Chen
:
Towards understanding sparse filtering: A theoretical perspective. Neural Networks 98: 154-177 (2018) - [c1]Fabio Massimo Zennaro
, Magdalena Ivanovska
:
Counterfactually Fair Prediction Using Multiple Causal Models. EUMAS 2018: 249-266 - [i4]Fabio Massimo Zennaro, Magdalena Ivanovska:
Pooling of Causal Models under Counterfactual Fairness via Causal Judgement Aggregation. CoRR abs/1805.09866 (2018) - [i3]Fabio Massimo Zennaro, Magdalena Ivanovska:
Counterfactually Fair Prediction Using Multiple Causal Models. CoRR abs/1810.00694 (2018) - 2017
- [b1]Fabio Massimo Zennaro:
Feature distribution learning for covariate shift adaptation using sparse filtering. University of Manchester, UK, 2017 - 2016
- [i2]Fabio Massimo Zennaro, Ke Chen:
Towards Understanding Sparse Filtering: A Theoretical Perspective. CoRR abs/1603.08831 (2016) - [i1]Fabio Massimo Zennaro, Ke Chen:
On Covariate Shift Adaptation via Sparse Filtering. CoRR abs/1607.06781 (2016)
Coauthor Index
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last updated on 2024-08-05 21:16 CEST by the dblp team
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