| Fast best subset selection: Coordinate descent and local combinatorial optimization algorithms H Hazimeh, R Mazumder Operations Research 68 (5), 1517-1537, 2020 | 129 | 2020 |
| Sparse regression at scale: Branch-and-bound rooted in first-order optimization H Hazimeh, R Mazumder, A Saab Mathematical Programming 196 (1-2), 347-388, 2022 | 47 | 2022 |
| The tree ensemble layer: Differentiability meets conditional computation H Hazimeh, N Ponomareva, P Mol, Z Tan, R Mazumder International Conference on Machine Learning, 4138-4148, 2020 | 40 | 2020 |
| Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning H Hazimeh, Z Zhao, A Chowdhery, M Sathiamoorthy, Y Chen, ... Advances in Neural Information Processing Systems 34, 2021 | 31 | 2021 |
| Learning sparse classifiers: Continuous and mixed integer optimization perspectives A Dedieu, H Hazimeh, R Mazumder The Journal of Machine Learning Research 22 (1), 6008-6054, 2021 | 30 | 2021 |
| Axiomatic analysis of smoothing methods in language models for pseudo-relevance feedback H Hazimeh, CX Zhai Proceedings of the 2015 international conference on the theory of …, 2015 | 29 | 2015 |
| Learning hierarchical interactions at scale: A convex optimization approach H Hazimeh, R Mazumder International Conference on Artificial Intelligence and Statistics, 1833-1843, 2020 | 13 | 2020 |
| Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives H Hazimeh, R Mazumder, P Radchenko The Annals of Statistics (to appear), 2021 | 11 | 2021 |
| L0Learn: A Scalable Package for Sparse Learning using L0 Regularization H Hazimeh, R Mazumder, T Nonet arXiv preprint arXiv:2202.04820, 2022 | 4* | 2022 |
| How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy N Ponomareva, H Hazimeh, A Kurakin, Z Xu, C Denison, HB McMahan, ... arXiv preprint arXiv:2303.00654, 2023 | 1 | 2023 |
| Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles S Ibrahim, H Hazimeh, R Mazumder Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 1 | 2022 |
| Fast as CHITA: Neural Network Pruning with Combinatorial Optimization R Benbaki, W Chen, X Meng, H Hazimeh, N Ponomareva, Z Zhao, ... arXiv preprint arXiv:2302.14623, 2023 | | 2023 |
| Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets H Hazimeh, N Ponomareva arXiv preprint arXiv:2302.00089, 2023 | | 2023 |
| Benchmarking Robustness to Adversarial Image Obfuscations F Stimberg, A Chakrabarti, CT Lu, H Hazimeh, O Stretcu, W Qiao, Y Liu, ... arXiv preprint arXiv:2301.12993, 2023 | | 2023 |
| Sparse and differentiable mixture of experts neural networks Z Zhao, M Sathiamoorthy, L Hong, Y Chen, EHH Chi, A Chowdhery, ... US Patent App. 17/665,279, 2022 | | 2022 |
| Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles S Ibrahim, H Hazimeh, R Mazumder KDD 2022, 2022 | | 2022 |
| Sparse Learning using Discrete Optimization: Scalable Algorithms and Statistical Insights H Hazimeh Massachusetts Institute of Technology, 2021 | | 2021 |
| Supplementary to “DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning” H Hazimeh, Z Zhao, A Chowdhery, M Sathiamoorthy, Y Chen, ... | | |
| Supplementary to “Learning Hierarchical Interactions at Scale: A Convex Optimization Approach” H Hazimeh, R Mazumder International Conference on Artificial Intelligence and Statistics, 1833-1843, 0 | | |
Rahul MazumderMassachusetts Institute of TechnologyVerified email at mit.edu
