| Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks WL Chiang, X Liu, S Si, Y Li, S Bengio, CJ Hsieh Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 1605 | 2019 |
| Bregman divergence-based regularization for transfer subspace learning S Si, D Tao, B Geng IEEE Transactions on Knowledge and Data Engineering 22 (7), 929-942, 2009 | 536 | 2009 |
| Scalable coordinate descent approaches to parallel matrix factorization for recommender systems HF Yu, CJ Hsieh, S Si, I Dhillon Data Mining (ICDM), 2012 IEEE 12th International Conference on, 765-774, 2012 | 344 | 2012 |
| A Divide-and-Conquer Solver for Kernel Support Vector Machines CJ Hsieh, S Si, IS Dhillon Proceedings of The 31st International Conference on Machine Learning, 566-574, 2014 | 218 | 2014 |
| Memory efficient kernel approximation S Si, CJ Hsieh, IS Dhillon Journal of Machine Learning Research 18 (20), 1-32, 2017 | 206 | 2017 |
| Parallel matrix factorization for recommender systems HF Yu, CJ Hsieh, S Si, IS Dhillon Knowledge and Information Systems 41, 793-819, 2014 | 181 | 2014 |
| Gradient boosted decision trees for high dimensional sparse output S Si, H Zhang, SS Keerthi, D Mahajan, IS Dhillon, CJ Hsieh International conference on machine learning, 3182-3190, 2017 | 178 | 2017 |
| Scaling up dataset distillation to imagenet-1k with constant memory J Cui, R Wang, S Si, CJ Hsieh International Conference on Machine Learning, 6565-6590, 2023 | 136 | 2023 |
| Neural sde: Stabilizing neural ode networks with stochastic noise X Liu, T Xiao, S Si, Q Cao, S Kumar, CJ Hsieh arXiv preprint arXiv:1906.02355, 2019 | 122 | 2019 |
| Robustness verification of tree-based models H Chen, H Zhang, S Si, Y Li, D Boning, CJ Hsieh Advances in Neural Information Processing Systems 32, 2019 | 114 | 2019 |
| You look twice: Gaternet for dynamic filter selection in cnns Z Chen, Y Li, S Bengio, S Si Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 108 | 2019 |
| A unified framework for data poisoning attack to graph-based semi-supervised learning X Liu, S Si, X Zhu, Y Li, CJ Hsieh arXiv preprint arXiv:1910.14147, 2019 | 105 | 2019 |
| Learnable fourier features for multi-dimensional spatial positional encoding Y Li, S Si, G Li, CJ Hsieh, S Bengio Advances in Neural Information Processing Systems 34, 15816-15829, 2021 | 97 | 2021 |
| GPU-acceleration for Large-scale Tree Boosting H Zhang, S Si, CJ Hsieh arXiv preprint arXiv:1706.08359, 2017 | 83 | 2017 |
| DC-BENCH: Dataset condensation benchmark J Cui, R Wang, S Si, CJ Hsieh Advances in Neural Information Processing Systems 35, 810-822, 2022 | 77 | 2022 |
| Fast prediction for large-scale kernel machines CJ Hsieh, S Si, IS Dhillon Advances in Neural Information Processing Systems 27, 2014 | 74 | 2014 |
| How does noise help robustness? explanation and exploration under the neural sde framework X Liu, T Xiao, S Si, Q Cao, S Kumar, CJ Hsieh Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 67 | 2020 |
| Goal-directed inductive matrix completion S Si, KY Chiang, CJ Hsieh, N Rao, IS Dhillon Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016 | 62 | 2016 |
| Groupreduce: Block-wise low-rank approximation for neural language model shrinking P Chen, S Si, Y Li, C Chelba, CJ Hsieh Advances in Neural Information Processing Systems 31, 2018 | 57 | 2018 |
| Multi-scale link prediction D Shin, S Si, IS Dhillon Proceedings of the 21st ACM international conference on Information and …, 2012 | 39 | 2012 |
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
