Marco Maggipinto

17 papers A* 1A 1C 1Misc 2Journal 9Unranked 3
YearRankTypeTitle / Venue / Authors
2023 J jnl
Lazy FSCA for unsupervised variable selection.
Eng. Appl. Artif. Intell.
Federico Zocco, Marco Maggipinto, Gian Antonio Susto, Seán F. McLoone
2022 J jnl
A Deep Convolutional Autoencoder-Based Approach for Anomaly Detection With Industrial, Non-Images, 2-Dimensional Data: A Semiconductor Manufacturing Case Study.
IEEE Trans Autom. Sci. Eng.
Marco Maggipinto, Alessandro Beghi, Gian Antonio Susto
2022 J jnl
IntroVAC: Introspective Variational Classifiers for learning interpretable latent subspaces.
Eng. Appl. Artif. Intell.
Marco Maggipinto, Matteo Terzi, Gian Antonio Susto
2021 A* conf
Adversarial Training Reduces Information and Improves Transferability.
AAAI
Matteo Terzi, Alessandro Achille, Marco Maggipinto, Gian Antonio Susto
2021 J jnl
Greedy Search Algorithms for Unsupervised Variable Selection: A Comparative Study.
CoRR
Federico Zocco, Marco Maggipinto, Gian Antonio Susto, Seán F. McLoone
2020 J jnl
Adversarial Training Reduces Information and Improves Transferability.
CoRR
Matteo Terzi, Alessandro Achille, Marco Maggipinto, Gian Antonio Susto
2020 J jnl
Induced Start Dynamic Sampling for Wafer Metrology Optimization.
IEEE Trans Autom. Sci. Eng.
Gian Antonio Susto, Marco Maggipinto, Federico Zocco, Seán F. McLoone
2020 Misc conf
Interpretable Anomaly Detection for Knowledge Discovery in Semiconductor Manufacturing.
WSC
Mattia Carletti, Marco Maggipinto, Alessandro Beghi, Gian Antonio Susto, Natalie Gentner, Yao Yang, Andreas Kyek
2020 J jnl
IntroVAC: Introspective Variational Classifiers for Learning Interpretable Latent Subspaces.
CoRR
Marco Maggipinto, Matteo Terzi, Gian Antonio Susto
2020 A conf
Proximal Deterministic Policy Gradient.
IROS
Marco Maggipinto, Gian Antonio Susto, Pratik Chaudhari
2020 J jnl
Proximal Deterministic Policy Gradient.
CoRR
Marco Maggipinto, Gian Antonio Susto, Pratik Chaudhari
2020 J jnl
β-Variational Classifiers Under Attack.
CoRR
Marco Maggipinto, Matteo Terzi, Gian Antonio Susto
2019 C conf
A Deep Learning-based Approach to Anomaly Detection with 2-Dimensional Data in Manufacturing.
INDIN
Marco Maggipinto, Alessandro Beghi, Gian Antonio Susto
2019 Misc conf
Probabilistic Word Embeddings in Neural IR: A Promising Model That Does Not Work as Expected (For Now).
ICTIR
Alberto Purpura, Marco Maggipinto, Gianmaria Silvello, Gian Antonio Susto
2019 — conf
What are the Most Informative Data for Virtual Metrology? A use case on Multi-Stage Processes Fault Prediction.
CASE
Marco Maggipinto, Gian Antonio Susto, Federico Zocco, Seán F. McLoone
2018 — conf
Machine Learning-based Laundry Weight Estimation for Vertical Axis Washing Machines.
ECC
Gian Antonio Susto, Marco Maggipinto, Giulia Zannon, Fabio Altinier, Elena Pesavento, Alessandro Beghi
2017 — conf
Deep learning for virtual metrology: Modeling with optical emission spectroscopy data.
RTSI
Matteo Terzi, Chiara Masiero, Alessandro Beghi, Marco Maggipinto, Gian Antonio Susto