| 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, ... Journal of Artificial Intelligence Research 77, 1113-1201, 2023 | 172 | 2023 |
| Shift-robust gnns: Overcoming the limitations of localized graph training data Q Zhu, N Ponomareva, J Han, B Perozzi Advances in Neural Information Processing Systems 34, 27965-27977, 2021 | 122 | 2021 |
| 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 | 113 | 2020 |
| Accelerating Gradient Boosting Machines H Lu, SP Karimireddy, N Ponomareva, V Mirrokni International Conference on Artificial Intelligence and Statistics, 516-526, 2020 | 51 | 2020 |
| Scaling laws for downstream task performance of large language models B Isik, N Ponomareva, H Hazimeh, D Paparas, S Vassilvitskii, S Koyejo arXiv preprint arXiv:2402.04177, 2024 | 36 | 2024 |
| Training Text-to-Text Transformers with Privacy Guarantees N Ponomareva, J Bastings, S Vassilvitskii Findings of the Association for Computational Linguistics: ACL 2022, 2182-2193, 2022 | 36 | 2022 |
| Privacy-preserving recommender systems with synthetic query generation using differentially private large language models AG Carranza, R Farahani, N Ponomareva, A Kurakin, M Jagielski, M Nasr arXiv preprint arXiv:2305.05973, 2023 | 34 | 2023 |
| Tf boosted trees: A scalable tensorflow based framework for gradient boosting N Ponomareva, S Radpour, G Hendry, S Haykal, T Colthurst, P Mitrichev, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 29 | 2017 |
| Harnessing large-language models to generate private synthetic text A Kurakin, N Ponomareva, U Syed, L MacDermed, A Terzis arXiv preprint arXiv:2306.01684, 2023 | 27 | 2023 |
| Compact multi-class boosted trees N Ponomareva, T Colthurst, G Hendry, S Haykal, S Radpour 2017 IEEE International Conference on Big Data (Big Data), 47-56, 2017 | 27 | 2017 |
| Fast as chita: Neural network pruning with combinatorial optimization R Benbaki, W Chen, X Meng, H Hazimeh, N Ponomareva, Z Zhao, ... International Conference on Machine Learning, 2031-2049, 2023 | 26 | 2023 |
| Agent prioritization for autonomous navigation KS Refaat, K Ding, N Ponomareva, S Ross 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 23 | 2019 |
| Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance S Ibrahim, N Ponomareva, R Mazumder Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 22 | 2022 |
| Explaining and Adapting Graph Conditional Shift Q Zhu, Y Jiao, N Ponomareva, J Han, B Perozzi arXiv preprint arXiv:2306.03256, 2023 | 14 | 2023 |
| How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy N Ponomareva, S Vassilvitskii, Z Xu, B McMahan, A Kurakin, C Zhang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 13 | 2023 |
| Methods, systems, and media for language identification of a media content item based on comments AS Doğruöz, N Ponomareva, CU Oehler, D Kanevsky US Patent 10,430,835, 2019 | 9 | 2019 |
| OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization X Meng, S Ibrahim, K Behdin, H Hazimeh, N Ponomareva, R Mazumder arXiv preprint arXiv:2403.12983, 2024 | 6 | 2024 |
| Comet: Learning cardinality constrained mixture of experts with trees and local search S Ibrahim, W Chen, H Hazimeh, N Ponomareva, Z Zhao, R Mazumder Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 4 | 2023 |
| Using agent-based modelling and backtest to evaluate algorithmic trading strategies N Ponomareva University of Oxford, 2011 | 4 | 2011 |
| Text based user comments as a signal for automatic language identification of online videos AS Doğruöz, N Ponomareva, S Girgin, R Jain, C Oehler Proceedings of the 19th ACM International Conference on Multimodal …, 2017 | 3 | 2017 |
Hussein HazimehGoogle Research - Massachusetts Institute of TechnologyE-mail megerősítve itt: mit.edu
