| A universal catalyst for first-order optimization H Lin, J Mairal, Z Harchaoui Advances in neural information processing systems 28, 2015 | 518 | 2015 |
| Resnet with one-neuron hidden layers is a universal approximator H Lin, S Jegelka Advances in neural information processing systems 31, 2018 | 304 | 2018 |
| Catalyst acceleration for first-order convex optimization: from theory to practice H Lin, J Mairal, Z Harchaoui Journal of Machine Learning Research 18 (212), 1-54, 2018 | 171 | 2018 |
| Complexity of finding stationary points of nonconvex nonsmooth functions J Zhang, H Lin, S Jegelka, S Sra, A Jadbabaie International Conference on Machine Learning, 11173-11182, 2020 | 117 | 2020 |
| Catalyst for gradient-based nonconvex optimization C Paquette, H Lin, D Drusvyatskiy, J Mairal, Z Harchaoui International Conference on Artificial Intelligence and Statistics, 613-622, 2018 | 104* | 2018 |
| Delayed gradient averaging: Tolerate the communication latency for federated learning L Zhu, H Lin, Y Lu, Y Lin, S Han Advances in neural information processing systems 34, 29995-30007, 2021 | 73 | 2021 |
| An inexact variable metric proximal point algorithm for generic quasi-Newton acceleration H Lin, J Mairal, Z Harchaoui SIAM Journal on Optimization 29 (2), 1408-1443, 2019 | 28* | 2019 |
| Ideal: Inexact decentralized accelerated augmented lagrangian method Y Arjevani, J Bruna, B Can, M Gürbüzbalaban, S Jegelka, H Lin Advances in Neural Information Processing Systems 33, 20648--20659, 2020 | 26 | 2020 |
| Deep hybrid model with satellite imagery: How to combine demand modeling and computer vision for travel behavior analysis? Q Wang, S Wang, Y Zheng, H Lin, X Zhang, J Zhao, J Walker Transportation Research Part B: Methodological 179, 102869, 2024 | 12 | 2024 |
| UNDIAL: Self-Distillation with Adjusted Logits for Robust Unlearning in Large Language Models YR Dong, H Lin, M Belkin, R Huerta, I Vulić arXiv preprint arXiv:2402.10052, 2024 | 11* | 2024 |
| Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity J Zhang, H Lin, S Das, S Sra, A Jadbabaie International Conference on Machine Learning, 26347-26361, 2022 | 6* | 2022 |
| On the complexity of minimizing convex finite sums without using the indices of the individual functions Y Arjevani, A Daniely, S Jegelka, H Lin arXiv preprint arXiv:2002.03273, 2020 | 3 | 2020 |
| Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving Y Lin, S Tang, B Lyu, J Wu, H Lin, K Yang, J Li, M Xia, D Chen, S Arora, ... arXiv preprint arXiv:2502.07640, 2025 | 2 | 2025 |
| From sparse dependence to sparse attention: unveiling how chain-of-thought enhances transformer sample efficiency K Wen, H Zhang, H Lin, J Zhang arXiv preprint arXiv:2410.05459, 2024 | 2 | 2024 |
| Perceptual regularization: Visualizing and learning generalizable representations H Lin, J Robinson, S Jegelka | 1 | 2019 |
| Task Generalization With AutoRegressive Compositional Structure: Can Learning From $\d $ Tasks Generalize to $\d^{T} $ Tasks? A Abedsoltan, H Zhang, K Wen, H Lin, J Zhang, M Belkin arXiv preprint arXiv:2502.08991, 2025 | | 2025 |
| Algorithmes d'accélération générique pour les méthodes d'optimisation en apprentissage statistique H Lin Université Grenoble Alpes (ComUE), 2017 | | 2017 |
Julien MairalInria - Univ. Grenoble AlpesVerified email at inria.fr
