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ORCIDKimia Nadjahi
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2020 – today
- 2024
[c11]Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola:
Federated Wasserstein Distance. ICLR 2024- [c10]Kimia Nadjahi, Kristjan H. Greenewald, Rickard Brüel Gabrielsson, Justin Solomon:
Slicing Mutual Information Generalization Bounds for Neural Networks. ICML 2024 - [c9]Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon:
Asymmetry in Low-Rank Adapters of Foundation Models. ICML 2024 - [i11]Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon:
Asymmetry in Low-Rank Adapters of Foundation Models. CoRR abs/2402.16842 (2024) - [i10]Kimia Nadjahi, Kristjan H. Greenewald, Rickard Brüel Gabrielsson, Justin Solomon:
Slicing Mutual Information Generalization Bounds for Neural Networks. CoRR abs/2406.04047 (2024) - 2023
- [c8]Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola:
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. ICML 2023: 26451-26473 - [i9]Thibault Séjourné, Clément Bonet, Kilian Fatras, Kimia Nadjahi, Nicolas Courty:
Unbalanced Optimal Transport meets Sliced-Wasserstein. CoRR abs/2306.07176 (2023) - [i8]Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola:
Federated Wasserstein Distance. CoRR abs/2310.01973 (2023) - 2022
- [c7]Soheil Kolouri, Kimia Nadjahi, Shahin Shahrampour, Umut Simsekli:
Generalized Sliced Probability Metrics. ICASSP 2022: 4513-4517 - [i7]Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola:
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. CoRR abs/2206.03230 (2022) - 2021
- [c6]Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli:
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. NeurIPS 2021: 12411-12424 - [i6]Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli:
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. CoRR abs/2106.15427 (2021) - 2020
- [c5]Kimia Nadjahi, Valentin De Bortoli, Alain Durmus, Roland Badeau, Umut Simsekli:
Approximate Bayesian Computation with the Sliced-Wasserstein Distance. ICASSP 2020: 5470-5474 - [c4]Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli:
Statistical and Topological Properties of Sliced Probability Divergences. NeurIPS 2020 - [i5]Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Shahin Shahrampour:
Generalized Sliced Distances for Probability Distributions. CoRR abs/2002.12537 (2020) - [i4]Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli:
Statistical and Topological Properties of Sliced Probability Divergences. CoRR abs/2003.05783 (2020)
2010 – 2019
- 2019
- [c3]Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau:
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. NeurIPS 2019: 250-260 - [c2]Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde:
Generalized Sliced Wasserstein Distances. NeurIPS 2019: 261-272 - [c1]Kimia Nadjahi, Romain Laroche, Rémi Tachet des Combes:
Safe Policy Improvement with Soft Baseline Bootstrapping. ECML/PKDD (3) 2019: 53-68 - [i3]Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde:
Generalized Sliced Wasserstein Distances. CoRR abs/1902.00434 (2019) - [i2]Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau:
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. CoRR abs/1906.04516 (2019) - [i1]Kimia Nadjahi, Romain Laroche, Rémi Tachet des Combes:
Safe Policy Improvement with Soft Baseline Bootstrapping. CoRR abs/1907.05079 (2019)
Coauthor Index
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