| High probability complexity bounds for line search based on stochastic oracles B Jin, K Scheinberg, M Xie Advances in Neural Information Processing Systems 34, 9193-9203, 2021 | 23 | 2021 |
| Controlburn: Feature selection by sparse forests B Liu, M Xie, M Udell Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 9 | 2021 |
| Stochastic adaptive regularization method with cubics: A high probability complexity bound K Scheinberg, M Xie 2023 Winter Simulation Conference (WSC), 3520-3531, 2023 | 7 | 2023 |
| A sequential quadratic programming method with high probability complexity bounds for nonlinear equality constrained stochastic optimization AS Berahas, M Xie, B Zhou arXiv preprint arXiv:2301.00477, 2023 | 7 | 2023 |
| Sample complexity analysis for adaptive optimization algorithms with stochastic oracles B Jin, K Scheinberg, M Xie Mathematical Programming, 1-29, 2024 | 4 | 2024 |
| High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles B Jin, K Scheinberg, M Xie arXiv preprint arXiv:2106.06454, 2022 | 4 | 2022 |
| A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers M Menickelly, SM Wild, M Xie arXiv preprint arXiv:2302.09128, 2023 | 3 | 2023 |
| Inner approximation of convex cones via primal-dual ellipsoidal norms M Xie University of Waterloo, 2016 | 3 | 2016 |
| ControlBurn: Nonlinear Feature Selection with Sparse Tree Ensembles B Liu, M Xie, H Yang, M Udell arXiv preprint arXiv:2207.03935, 2022 | 1 | 2022 |
| High Probability Step Size Lower Bound for Adaptive Stochastic Optimization B Jin, K Scheinberg, M Xie OPT 2021: Optimization for Machine Learning (NeurIPS 2021 Workshop), 0 | | |
Katya ScheinbergCornell UniversityVahvistettu sähköpostiosoite verkkotunnuksessa cornell.edu
