Fast quantum state reconstruction via accelerated non-convex programming JL Kim, G Kollias, A Kalev, KX Wei, A Kyrillidis Photonics 10 (2), 116, 2023 | 9 | 2023 |
Convergence and stability of the stochastic proximal point algorithm with momentum JL Kim, P Toulis, A Kyrillidis Learning for Dynamics and Control Conference, 1034-1047, 2022 | 8 | 2022 |
Adaptive federated learning with auto-tuned clients JL Kim, MT Toghani, CA Uribe, A Kyrillidis arXiv preprint arXiv:2306.11201, 2023 | 4 | 2023 |
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography JL Kim, MT Toghani, CA Uribe, A Kyrillidis IEEE Control Systems Letters 7, 199-204, 2022 | 2 | 2022 |
How much pre-training is enough to discover a good subnetwork? CR Wolfe, Q Wang, JL Kim, A Kyrillidis | 2 | 2021 |
When is Momentum Extragradient Optimal? A Polynomial-Based Analysis JL Kim, G Gidel, A Kyrillidis, F Pedregosa arXiv preprint arXiv:2211.04659, 2022 | 1* | 2022 |
Momentum Extragradient is Optimal for Games with Cross-Shaped Spectrum JL Kim, G Gidel, A Kyrillidis, F Pedregosa OPT 2022: Optimization for Machine Learning (NeurIPS 2022 Workshop), 2022 | 1 | 2022 |
Package ‘sgd’ JL Kim, D Tran, P Toulis, T Lian, Y Kuang, E Airoldi | | 2024 |
On the Error-Propagation of Inexact Deflation for Principal Component Analysis F Liao, JL Kim, C Barnum, A Kyrillidis arXiv preprint arXiv:2310.04283, 2023 | | 2023 |
Adaptive Federated Learning with Auto-Tuned Clients via Local Smoothness JL Kim, T Toghani, CA Uribe, A Kyrillidis Federated Learning and Analytics in Practice: Algorithms, Systems …, 2023 | | 2023 |
Acceleration and Stability of the Stochastic Proximal Point Algorithm JL Kim, P Toulis, A Kyrillidis NeurIPS 2021 Workshop on Optimization for Machine Learning, 2021 | | 2021 |
Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs JL Kim, JA Benitez, MT Toghani, C Wolfe, Z Zhang, A Kyrillidis arXiv preprint arXiv:2106.08775, 2021 | | 2021 |