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ORCIDGiorgia Franchini
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2020 – today
- 2026
[j15]Mauro Dell'Amico
, Giorgia Franchini, Matteo Magnani, Luca Zanni:
Can machine learning help in solving the pallet loading optimization problem? J. Heuristics 32(1): 11 (2026)- [j14]Filippo Camellini, Serena Crisci, Anna De Magistris, Giorgia Franchini:
A line-search based SGD algorithm with Adaptive Importance Sampling. J. Comput. Appl. Math. 477: 117120 (2026) - 2025
- [j13]Filippo Camellini, Giorgia Franchini, Marco Prato:
Computing p th root of a transition matrix with a deep unsupervised learning approach. Int. J. Comput. Math. 102(4): 577-594 (2025) - [j12]Silvia Bonettini, Giorgia Franchini, Danilo Pezzi, Marco Prato:
Linesearch-Enhanced Forward-Backward Methods for Inexact Nonconvex Scenarios. SIAM J. Imaging Sci. 18(2): 1314-1343 (2025) - [j11]Alessandro Benfenati, Ambra Catozzi, Giorgia Franchini, Federica Porta:
Early stopping strategies in Deep Image Prior. Soft Comput. 29(8): 4153-4174 (2025) - [c15]Carmelo Scribano, Elena Govi, Paolo Bertellini, Simone Parisi, Giorgia Franchini, Marko Bertogna:
Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation. ICIAP (2) 2025: 115-126 - [i9]Carmelo Scribano, Elena Govi, Paolo Bertellini, Simone Parisi, Giorgia Franchini, Marko Bertogna:
Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation. CoRR abs/2506.16318 (2025) - 2024
- [j10]Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta, Andrea Sebastiani:
A variable metric proximal stochastic gradient method: An application to classification problems. EURO J. Comput. Optim. 12: 100088 (2024) - [j9]Giorgia Franchini, Federica Porta, Valeria Ruggiero, Ilaria Trombini, Luca Zanni:
A stochastic gradient method with variance control and variable learning rate for Deep Learning. J. Comput. Appl. Math. 451: 116083 (2024) - 2023
- [j8]Carmelo Scribano, Danilo Pezzi, Giorgia Franchini, Marco Prato:
Denoising Diffusion Models on Model-Based Latent Space. Algorithms 16(11): 501 (2023) - [j7]Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta, Andrea Sebastiani:
Constrained and unconstrained deep image prior optimization models with automatic regularization. Comput. Optim. Appl. 84(1): 125-149 (2023) - [j6]Giorgia Franchini, Federica Porta, Valeria Ruggiero, Ilaria Trombini:
A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction. J. Sci. Comput. 94(1): 23 (2023) - [j5]Carmelo Scribano, Giorgia Franchini, Marco Prato, Marko Bertogna:
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform. J. Sci. Comput. 94(3): 67 (2023) - [j4]Giorgia Franchini, Federica Porta, Valeria Ruggiero, Ilaria Trombini:
Correction to: A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction. J. Sci. Comput. 96(2): 48 (2023) - [c14]Paolo Bertellini, Gianluca D'Addese, Giorgia Franchini, Simone Parisi, Carmelo Scribano, Daniele Zanirato, Marko Bertogna:
Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques. FedCSIS 2023: 859-864 - [c13]Giorgia Franchini, Federica Porta, Valeria Ruggiero, Ilaria Trombini, Luca Zanni:
Line Search Stochastic Gradient Algorithm with A-priori Rule for Monitoring the Control of the Variance. NUMTA (1) 2023: 94-107 - [c12]Matteo Magnani, Giorgia Franchini, Mauro Dell'Amico, Luca Zanni:
A Machine Learning Approach to Speed up the Solution of the Distributor's Pallet Loading Problem. NUMTA (1) 2023: 108-120 - [c11]Giorgia Franchini, Federica Porta, Valeria Ruggiero, Ilaria Trombini, Luca Zanni:
Diagonal Barzilai-Borwein Rules in Stochastic Gradient-Like Methods. OLA 2023: 21-35 - [c10]Alessio Masola, Nicola Capodieci, Benjamin Rouxel, Giorgia Franchini, Roberto Cavicchioli:
Machine Learning Techniques for Understanding and Predicting Memory Interference in CPU-GPU Embedded Systems. RTCSA 2023: 147-156 - [c9]Alessandro Benfenati, Ambra Catozzi, Giorgia Franchini, Federica Porta:
Piece-wise Constant Image Segmentation with a Deep Image Prior Approach. SSVM 2023: 352-362 - [i8]Davide Sapienza, Elena Govi, Sara Aldhaheri, Giorgia Franchini, Marko Bertogna, Eloy Roura, Èric Pairet, Micaela Verucchi, Paola Ardón:
Model-Based Underwater 6D Pose Estimation from RGB. CoRR abs/2302.06821 (2023) - [i7]Elena Govi, Davide Sapienza, Carmelo Scribano, Tobia Poppi, Giorgia Franchini, Paola Ardón, Micaela Verucchi, Marko Bertogna:
Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation. CoRR abs/2304.08230 (2023) - [i6]Alessandro Benfenati, Emilie Chouzenoux, Giorgia Franchini, Salla Latva-Aijo, Dominik Narnhofer, Jean-Christophe Pesquet, Sebastian J. Scott, Mahsa Yousefi:
Majorization-Minimization for sparse SVMs. CoRR abs/2308.16858 (2023) - 2022
- [j3]Giorgia Franchini, Micaela Verucchi, Ambra Catozzi, Federica Porta, Marco Prato:
Biomedical Image Classification via Dynamically Early Stopped Artificial Neural Network. Algorithms 15(10): 386 (2022) - [j2]Davide Sapienza, Giorgia Franchini, Elena Govi, Marko Bertogna, Marco Prato:
Deep Image Prior for medical image denoising, a study about parameter initialization. Frontiers Appl. Math. Stat. 8 (2022) - [c8]Silvia Bonettini, Giorgia Franchini, Danilo Pezzi, Marco Prato:
Learning the Image Prior by Unrolling an Optimization Method. EUSIPCO 2022: 952-956 - [i5]Carmelo Scribano, Giorgia Franchini, Marco Prato, Marko Bertogna:
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform. CoRR abs/2203.01178 (2022) - [i4]Carmelo Scribano, Giorgia Franchini, Ignacio Sañudo Olmedo, Marko Bertogna:
CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning. CoRR abs/2210.00756 (2022) - [i3]Silvia Bonettini, Giorgia Franchini, Danilo Pezzi, Marco Prato:
Explainable bilevel optimization: an application to the Helsinki deblur challenge. CoRR abs/2210.10050 (2022) - 2021
- [c7]Carmelo Scribano, Davide Sapienza, Giorgia Franchini, Micaela Verucchi, Marko Bertogna:
All You Can Embed: Natural Language Based Vehicle Retrieval With Spatio-Temporal Transformers. CVPR Workshops 2021: 4253-4262 - [c6]Pasquale Cascarano, Andrea Sebastiani, Maria Colomba Comes, Giorgia Franchini, Federica Porta:
Combining Weighted Total Variation and Deep Image Prior for natural and medical image restoration via ADMM. ICCSA (Workshops) 2021: 39-46 - [c5]Giorgia Franchini, Valeria Ruggiero, Ilaria Trombini:
Thresholding Procedure via Barzilai-Borwein Rules for the Steplength Selection in Stochastic Gradient Methods. LOD 2021: 277-282 - [i2]Carmelo Scribano, Davide Sapienza, Giorgia Franchini, Micaela Verucchi, Marko Bertogna:
All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers. CoRR abs/2106.10153 (2021) - 2020
- [j1]Giorgia Franchini, Valeria Ruggiero, Luca Zanni:
Ritz-like values in steplength selections for stochastic gradient methods. Soft Comput. 24(23): 17573-17588 (2020) - [c4]Giorgia Franchini, Valeria Ruggiero, Luca Zanni:
Steplength and Mini-batch Size Selection in Stochastic Gradient Methods. LOD (2) 2020: 259-263
2010 – 2019
- 2019
- [c3]Giorgia Franchini, Mathilde Galinier, Micaela Verucchi:
Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning. INNSBDDL 2019: 286-295 - [c2]Giorgia Franchini, Valeria Ruggiero, Luca Zanni:
On the Steplength Selection in Stochastic Gradient Methods. NUMTA(1) 2019: 186-197 - [i1]Giorgia Franchini, Mathilde Galinier, Micaela Verucchi:
Mise en abyme with artificial intelligence: how to predict the accuracy of NN, applied to hyper-parameter tuning. CoRR abs/1907.00924 (2019) - 2018
- [c1]Giorgia Franchini, Paolo Burgio, Luca Zanni:
Artificial Neural Networks: The Missing Link Between Curiosity and Accuracy. ISDA (2) 2018: 1025-1034
Coauthor Index
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last updated on 2026-03-10 23:03 CET by the dblp team
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