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Luca Ganassali
Luca Ganassali
Université Paris-Saclay, Laboratoire de Mathématiques d'Orsay
Adresă de e-mail confirmată pe universite-paris-saclay.fr - Pagina de pornire
Titlu
Citat de
Citat de
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From tree matching to sparse graph alignment
L Ganassali, L Massoulié
Conference on Learning Theory, 1633-1665, 2020
49*2020
Impossibility of Partial Recovery in the Graph Alignment Problem
L Ganassali, L Massoulié, M Lelarge
Conference on Learning Theory 134, 2080-2102, 2021
48*2021
Correlation Detection in Trees for Planted Graph Alignment
L Ganassali, L Massoulié, M Lelarge
13th Innovations in Theoretical Computer Science Conference (ITCS 2022) 215 …, 2021
24*2021
Sharp threshold for alignment of graph databases with Gaussian weights
L Ganassali
Mathematical and Scientific Machine Learning (MSML21), 2020
222020
Statistical limits of correlation detection in trees
L Ganassali, L Massoulié, G Semerjian
arXiv preprint arXiv:2209.13723, 2022
202022
Spectral alignment of correlated gaussian random matrices
L Ganassali, M Lelarge, L Massoulié
Advances in Applied Probability 54 (1), 2019
18*2019
Causal discovery via monotone triangular transport maps
S Akbari, L Ganassali, N Kiyavash
NeurIPS 2023 Workshop Optimal Transport and Machine Learning, 2023
10*2023
Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing
M Akian, L Ganassali, S Gaubert, L Massoulié
arXiv preprint arXiv:2009.05304, 2020
82020
On sample complexity of conditional independence testing with von mises estimator with application to causal discovery
F Jamshidi, L Ganassali, N Kiyavash
arXiv preprint arXiv:2310.13553, 2023
32023
The graph alignment problem: fundamental limits and efficient algorithms
L Ganassali
arXiv preprint arXiv:2404.12418, 2024
22024
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem
M Even, L Ganassali, J Maier, L Massoulié
Advances in Neural Information Processing Systems 37, 70730-70764, 2025
12025
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