| An agnostic approach to federated learning with class imbalance Z Shen, J Cervino, H Hassani, A Ribeiro International Conference on Learning Representations, 2021 | 63 | 2021 |
| Learning by transference: Training graph neural networks on growing graphs J Cervino, L Ruiz, A Ribeiro IEEE Transactions on Signal Processing 71, 233-247, 2023 | 15 | 2023 |
| Training stable graph neural networks through constrained learning J Cerviño, L Ruiz, A Ribeiro ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 12 | 2022 |
| Multi-task reinforcement learning in reproducing kernel hilbert spaces via cross-learning J Cervino, JA Bazerque, M Calvo-Fullana, A Ribeiro IEEE Transactions on Signal Processing 69, 5947-5962, 2021 | 8 | 2021 |
| Learning globally smooth functions on manifolds J Cervino, LFO Chamon, BD Haeffele, R Vidal, A Ribeiro International Conference on Machine Learning, 3815-3854, 2023 | 7 | 2023 |
| A Manifold Perspective on the Statistical Generalization of Graph Neural Networks Z Wang, J Cervino, A Ribeiro arXiv preprint arXiv:2406.05225, 2024 | 6 | 2024 |
| Training graph neural networks on growing stochastic graphs J Cervino, L Ruiz, A Ribeiro ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 6 | 2023 |
| Meta-learning through coupled optimization in reproducing kernel hilbert spaces J Cerviño, JA Bazerque, M Calvo-Fullana, A Ribeiro 2019 American Control Conference (ACC), 4840-4846, 2019 | 5 | 2019 |
| Multi-task supervised learning via cross-learning J Cerviño, JA Bazerque, M Calvo-Fullana, A Ribeiro 2021 29th European Signal Processing Conference (EUSIPCO), 1381-1385, 2021 | 3 | 2021 |
| Increase and conquer: Training graph neural networks on growing graphs J Cervino, L Ruiz, A Ribeiro | 3 | 2021 |
| Generalization of geometric graph neural networks Z Wang, J Cervino, A Ribeiro arXiv preprint arXiv:2409.05191, 2024 | 2 | 2024 |
| FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs H Mostafa, A Grabowski, MA Turja, J Cervino, A Ribeiro, N Himayat arXiv preprint arXiv:2311.17847, 2023 | 2 | 2023 |
| Intrinsically motivated graph exploration using network theories of human curiosity SP Patankar, M Ouellet, J Cervino, A Ribeiro, KA Murphy, DS Bassett arXiv preprint arXiv:2307.04962, 2023 | 2 | 2023 |
| Multi-Task Bias-Variance Trade-Off Through Functional Constraints J Cerviño, JA Bazerque, M Calvo-Fullana, A Ribeiro ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 2 | 2023 |
| Generalization of Graph Neural Networks is Robust to Model Mismatch Z Wang, J Cervino, A Ribeiro arXiv preprint arXiv:2408.13878, 2024 | 1 | 2024 |
| Distributed training of large graph neural networks with variable communication rates J Cervino, MA Turja, H Mostafa, N Himayat, A Ribeiro arXiv preprint arXiv:2406.17611, 2024 | 1 | 2024 |
| Federated Representation Learning via Maximal Coding Rate Reduction J Cervino, N NaderiAlizadeh, A Ribeiro arXiv preprint arXiv:2210.00299, 2022 | 1 | 2022 |
| Parameter Critic: a Model Free Variance Reduction Method Through Imperishable Samples J Cervino, H Kumar, A Ribeiro arXiv preprint arXiv:2009.13668, 2020 | 1 | 2020 |
| Constrained Learning for Decentralized Multi-Objective Coverage Control J Cervino, S Agarwal, V Kumar, A Ribeiro arXiv preprint arXiv:2409.11311, 2024 | | 2024 |
Alejandro RibeiroUniversity of Pennsylvania在 seas.upenn.edu 的电子邮件经过验证
