| Only train once: A one-shot neural network training and pruning framework T Chen, B Ji, T Ding, B Fang, G Wang, Z Zhu, L Liang, Y Shi, S Yi, X Tu Advances in Neural Information Processing Systems 34, 19637-19651, 2021 | 102 | 2021 |
| Approximation algorithms for training one-node ReLU neural networks SS Dey, G Wang, Y Xie IEEE Transactions on Signal Processing 68, 6696-6706, 2020 | 30 | 2020 |
| Orthant Based Proximal Stochastic Gradient Method for -Regularized Optimization T Chen, T Ding, B Ji, G Wang, Y Shi, J Tian, S Yi, X Tu, Z Zhu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 26 | 2021 |
| A convex integer programming approach for optimal sparse pca SS Dey, R Mazumder, G Wang arXiv preprint arXiv:1810.09062, 2018 | 23 | 2018 |
| Using -Relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA SS Dey, R Mazumder, G Wang Operations Research 70 (3), 1914-1932, 2022 | 21 | 2022 |
| Half-space proximal stochastic gradient method for group-sparsity regularized problem T Chen, G Wang, T Ding, B Ji, S Yi, Z Zhu arXiv preprint arXiv:2009.12078, 2020 | 9 | 2020 |
| Mixed-integer linear representability, disjunctions, and variable elimination A Basu, K Martin, CT Ryan, G Wang International Conference on Integer Programming and Combinatorial …, 2017 | 9 | 2017 |
| A framework for fair decision-making over time with time-invariant utilities A Lodi, S Sankaranarayanan, G Wang European Journal of Operational Research 319 (2), 456-467, 2024 | 7 | 2024 |
| An adaptive half-space projection method for stochastic optimization problems with group sparse regularization Y Dai, T Chen, G Wang, DP Robinson Transactions on machine learning research, 2023 | 7 | 2023 |
| Solving sparse principal component analysis with global support SS Dey, M Molinaro, G Wang Mathematical Programming 199 (1), 421-459, 2023 | 7 | 2023 |
| Upper bounds for model-free row-sparse principal component analysis G Wang, S Dey International Conference on Machine Learning, 9868-9875, 2020 | 6 | 2020 |
| Sparse principal component analysis and its -relaxation SS Dey, R Mazumder, M Molinaro, G Wang arXiv preprint arXiv:1712.00800, 2017 | 4 | 2017 |
| Solving row-sparse principal component analysis via convex integer programs SS Dey, M Molinaro, G Wang arXiv preprint arXiv:2010.11152, 2020 | 3 | 2020 |
| A Half-Space Stochastic Projected Gradient Method for Group Sparsity Regularization T Chen, G Wang, D Tianyu, B Ji, S Yi, Z Zhu | 2 | 2020 |
| The strength of multi-row aggregation cuts for sign-pattern integer programs SS Dey, A Iroume, G Wang Operations Research Letters 46 (6), 611-615, 2018 | 2 | 2018 |
| Relu regression: Complexity, exact and approximation algorithms SS Dey, G Wang, Y Xie arXiv preprint arXiv:1810.03592, 2018 | 2 | 2018 |
| Do algorithms and barriers for sparse principal component analysis extend to other structured settings? G Wang, M Lou, A Pananjady IEEE Transactions on Signal Processing, 2024 | 1 | 2024 |
| A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization Y Dai, G Wang, FE Curtis, DP Robinson International Conference on Artificial Intelligence and Statistics, 5107-5133, 2023 | 1 | 2023 |
| A simple algorithm for online decision making R Chen, O Gunluk, A Lodi, G Wang arXiv preprint arXiv:2211.03997, 2022 | 1 | 2022 |
| Mixed-integer linear representability, disjunctions, and Chvátal functions—Modeling implications A Basu, K Martin, CT Ryan, G Wang Mathematics of Operations Research 44 (4), 1264-1285, 2019 | 1 | 2019 |
Santanu S. DeyGeorgia Institute of Technology在 isye.gatech.edu 的电子邮件经过验证
