Luca Pasa

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 32

Top Topics

Top Venues

Publications

Pier Paolo Tricomi, Luca Pajola, Luca Pasa, Mauro Conti
"All of Me": Mining Users' Attributes from their Public Spotify Playlists. CoRR (2024)
Paolo Frazzetto, Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Beyond the Additive Nodes' Convolutions: a Study on High-Order Multiplicative Integration. SAC (2024)
Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti
A unified framework for backpropagation-free soft and hard gated graph neural networks. Knowl. Inf. Syst. 66 (4) (2024)
Danilo Franco, Vincenzo Stefano D'Amato, Luca Pasa, Nicolò Navarin, Luca Oneto
Fair graph representation learning: Empowering NIFTY via Biased Edge Dropout and Fair Attribute Preprocessing. Neurocomputing 563 (2024)
Giovanni Donghi, Luca Pasa, Luca Oneto, Claudio Gallicchio, Alessio Micheli, Davide Anguita, Alessandro Sperduti, Nicolò Navarin
Investigating over-parameterized randomized graph networks. Neurocomputing 606 (2024)
Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti
Empowering Simple Graph Convolutional Networks. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Pier Paolo Tricomi, Luca Pajola, Luca Pasa, Mauro Conti
"All of Me": Mining Users' Attributes from their Public Spotify Playlists. WWW (Companion Volume) (2024)
Paolo Frazzetto, Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Topology preserving maps as aggregations for Graph Convolutional Neural Networks. SAC (2023)
Davide Bacciu, Federico Errica, Alessio Micheli, Nicolò Navarin, Luca Pasa, Marco Podda, Daniele Zambon
Graph Representation Learning. ESANN (2023)
Nicolò Navarin, Luca Pasa, Luca Oneto, Alessandro Sperduti
An Empirical Study of Over-Parameterized Neural Models based on Graph Random Features. ESANN (2023)
Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti
Backpropagation-free Graph Neural Networks. ICDM (2022)
Davide Bacciu, Federico Errica, Nicolò Navarin, Luca Pasa, Daniele Zambon
Deep Learning for Graphs. ESANN (2022)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Multiresolution Reservoir Graph Neural Network. IEEE Trans. Neural Networks Learn. Syst. 33 (6) (2022)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Polynomial-based graph convolutional neural networks for graph classification. Mach. Learn. 111 (4) (2022)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Compact graph neural network models for node classification. SAC (2022)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
SOM-based aggregation for graph convolutional neural networks. Neural Comput. Appl. 34 (1) (2022)
Federico Caldart, Luca Pasa, Luca Oneto, Alessandro Sperduti, Nicolò Navarin
Biased Edge Dropout in NIFTY for Fair Graph Representation Learning. ESANN (2022)
Matteo Munari, Luca Pasa, Daniele Zambon, Cesare Alippi, Nicolò Navarin
Understanding Catastrophic Forgetting of Gated Linear Networks in Continual Learning. IJCNN (2022)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Tangent Graph Convolutional Network. ESANN (2021)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Simple Multi-resolution Gated GNN. SSCI (2021)
Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti
Simple Graph Convolutional Networks. CoRR (2021)
Ander Arriandiaga, Giovanni Morrone, Luca Pasa, Leonardo Badino, Chiara Bartolozzi
Audio-Visual Target Speaker Enhancement on Multi-Talker Environment Using Event-Driven Cameras. ISCAS (2021)
Luca Pasa, Nicolò Navarin, Alessandro Sperduti
Deep Recurrent Graph Neural Networks. ESANN (2020)
Luca Pasa, Giovanni Morrone, Leonardo Badino
An Analysis of Speech Enhancement and Recognition Losses in Limited Resources Multi-Talker Single Channel Audio-Visual ASR. ICASSP (2020)
Nicolò Navarin, Wolfgang Erb, Luca Pasa, Alessandro Sperduti
Linear Graph Convolutional Networks. ESANN (2020)
Giovanni Morrone, Sonia Bergamaschi, Luca Pasa, Luciano Fadiga, Vadim Tikhanoff, Leonardo Badino
Face Landmark-based Speaker-independent Audio-visual Speech Enhancement in Multi-talker Environments. ICASSP (2019)
Luca Pasa, Giovanni Morrone, Leonardo Badino
Joined Audio-Visual Speech Enhancement and Recognition in the Cocktail Party: The Tug Of War Between Enhancement and Recognition Losses. CoRR (2019)
Luca Pajola, Luca Pasa, Mauro Conti
Threat is in the Air: Machine Learning for Wireless Network Applications. WiseML@WiSec (2019)
Ander Arriandiaga, Giovanni Morrone, Luca Pasa, Leonardo Badino, Chiara Bartolozzi
Audio-Visual Target Speaker Extraction on Multi-Talker Environment using Event-Driven Cameras. CoRR (2019)
Giovanni Morrone, Luca Pasa, Vadim Tikhanoff, Sonia Bergamaschi, Luciano Fadiga, Leonardo Badino
Face Landmark-based Speaker-Independent Audio-Visual Speech Enhancement in Multi-Talker Environments. CoRR (2018)
Luca Pasa, Alessandro Sperduti, Peter Tiño
Linear dynamical based models for sequential domains. IJCNN (2017)
Luca Pasa, Alessandro Sperduti
Learning Sequential Data with the Help of Linear Systems. ANNPR (2016)
Luca Pasa, Alberto Testolin, Alessandro Sperduti
Neural Networks for Sequential Data: a Pre-training Approach based on Hidden Markov Models. Neurocomputing 169 (2015)
Luca Pasa, Alessandro Sperduti
Pre-training of Recurrent Neural Networks via Linear Autoencoders. NIPS (2014)
Luca Pasa, Alberto Testolin, Alessandro Sperduti
A HMM-based pre-training approach for sequential data. ESANN (2014)