| 2025 | ICLR | Scaling Laws for Downstream Task Performance in Machine Translation. | Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo |
| 2025 | KDD | SPARTA: An Optimization Framework for Differentially Private Sparse Fine-Tuning. | Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Rahul Mazumder, Hussein Hazimeh |
| 2024 | EMNLP | Private prediction for large-scale synthetic text generation. | Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii |
| 2024 | ICML | OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. | Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder |
| 2024 | NAACL | Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models. | Aldo G. Carranza, Rezsa Farahani, Natalia Ponomareva, Alexey Kurakin, Matthew Jagielski, Milad Nasr |
| 2023 | AISTATS | Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets. | Hussein Hazimeh, Natalia Ponomareva |
| 2023 | ICML | Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. | Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder |
| 2023 | KDD | COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. | Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder |
| 2023 | KDD | How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. | Natalia Ponomareva, Sergei Vassilvitskii, Zheng Xu, Brendan McMahan, Alexey Kurakin, Chiyaun Zhang |
| 2022 | ACL | Training Text-to-Text Transformers with Privacy Guarantees. | Natalia Ponomareva, Jasmijn Bastings, Sergei Vassilvitskii |
| 2020 | AISTATS | Accelerating Gradient Boosting Machines. | Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni |
| 2020 | ICML | The Tree Ensemble Layer: Differentiability meets Conditional Computation. | Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder |
| 2019 | IROS | Agent Prioritization for Autonomous Navigation. | Khaled S. Refaat, Kai Ding, Natalia Ponomareva, Stphane Ross |
| 2019 | RANLP | A Survey of the Perceived Text Adaptation Needs of Adults with Autism. | Victoria Yaneva, Constantin Orasan, Le An Ha, Natalia Ponomareva |
| 2017 | ICMI | Text based user comments as a signal for automatic language identification of online videos. | A. Seza Dogruz, Natalia Ponomareva, Sertan Girgin, Reshu Jain, Christoph Oehler |
| 2015 | CloudCom | A Classifier for the Latency-CPU Behaviors of Serving Jobs in Distributed Environments. | Christophe Restif, Natalia Ponomareva, Krzysztof Ostrowski |
| 2013 | RANLP | Semi-supervised vs. Cross-domain Graphs for Sentiment Analysis. | Natalia Ponomareva, Mike Thelwall |
| 2012 | CICLING | Biographies or Blenders: Which Resource Is Best for Cross-Domain Sentiment Analysis? | Natalia Ponomareva, Mike Thelwall |
| 2012 | EMNLP | Do Neighbours Help? An Exploration of Graph-based Algorithms for Cross-domain Sentiment Classification. | Natalia Ponomareva, Mike Thelwall |
| 2012 | ICECCS | Extending and Evaluating Agent-Based Models of Algorithmic Trading Strategies. | Natalia Ponomareva, Anisoara Calinescu |
| 2009 | NLDB | AIR: A Semi-Automatic System for Archiving Institutional Repositories. | Natalia Ponomareva, Jos Manuel Gmez Soriano, Viktor Pekar |
| 2007 | NLDB | Biomedical Named Entity Recognition: A Poor Knowledge HMM-Based Approach. | Natalia Ponomareva, Ferran Pla, Antonio Molina, Paolo Rosso |