| Fast and furious convergence: Stochastic second order methods under interpolation SY Meng, S Vaswani, IH Laradji, M Schmidt, S Lacoste-Julien International Conference on Artificial Intelligence and Statistics, 1375-1386, 2020 | 42 | 2020 |
| UD Co-Spaces: A Table-Centred Multi-Display Environment for Public Engagement in Urban Design Charrettes N Mahyar, KJ Burke, JE Xiang, SC Meng, KS Booth, CL Girling, ... Proceedings of the 2016 ACM International Conference on Interactive Surfaces …, 2016 | 32 | 2016 |
| A general analysis of example-selection for stochastic gradient descent Y Lu, SY Meng, C De Sa International Conference on Learning Representations (ICLR) 10, 2022 | 23 | 2022 |
| Adaptive gradient methods converge faster with over-parameterization (and you can do a line-search) S Vaswani, IH Laradji, F Kunstner, SY Meng, M Schmidt, S Lacoste-Julien | 23 | 2020 |
| A model-based method for minimizing CVaR and beyond SY Meng, RM Gower International Conference on Machine Learning, 24436-24456, 2023 | 5 | 2023 |
| Stochastic second-order optimization for over-parameterized machine learning models SY Meng University of British Columbia, 2020 | 3 | 2020 |
| Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes SY Meng, A Orvieto, DY Cao, C De Sa arXiv preprint arXiv:2406.05033, 2024 | 1 | 2024 |
| A Stochastic Prox-Linear Method for CVaR Minimization SY Meng, V Charisopoulos, RM Gower OPT 2022: Optimization for Machine Learning (NeurIPS 2022 Workshop), 2022 | 1 | 2022 |
