Daniele Zambon
TittelSitert avÅr
Concept drift and anomaly detection in graph streams
D Zambon, C Alippi, L Livi
IEEE transactions on neural networks and learning systems 29 (11), 5592-5605, 2018
212018
Ecg monitoring in wearable devices by sparse models
D Carrera, B Rossi, D Zambon, P Fragneto, G Boracchi
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016
92016
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds
D Grattarola, D Zambon, C Alippi, L Livi
IEEE Transactions on Neural Networks and Learning Systems, 2019
6*2019
Detecting changes in sequences of attributed graphs
D Zambon, L Livi, C Alippi
2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017
52017
Anomaly and Change Detection in Graph Streams through Constant-Curvature Manifold Embeddings
D Zambon, L Livi, C Alippi
2018 International Joint Conference on Neural Networks (IJCNN), 2018
22018
Change-Point Methods on a Sequence of Graphs
D Zambon, C Alippi, L Livi
IEEE Transactions on Signal Processing 67 (24), 6327-6341, 2019
12019
Distance-preserving graph embeddings from random neural features
D Zambon, C Alippi, L Livi
arXiv preprint arXiv:1909.03790, 2019
12019
Autoregressive Models for Sequences of Graphs
D Zambon, D Grattarola, L Livi, C Alippi
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
2019
Method for the detecting electrocardiogram anomalies and corresponding system
B Rossi, P Fragneto, D Carrera, G Boracchi, D Zambon
US Patent App. 15/696,051, 2017
2017
Method for the detecting electrocardiogram anomalies and corresponding system
B Rossi, P Fragneto, D Zambon, D Carrera, G Boracchi
US Patent App. 15/169,184, 2017
2017
METHOD FOR THE DETECTING ELECTROCARDIOGRAM ANOMALIES AND CORRESPONDING SYSTEM
G Boracchi, D Carrera, P Fragneto, B Rossi, D Zambon
2016
Graph Embeddings from Random Neural Features
D Zambon, C Alippi, L Livi
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Artikler 1–12