Natalia Ponomareva

46 papers A* 7A 3B 1C 1Journal 25Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Decomposing Private Image Generation via Coarse-to-Fine Wavelet Modeling. CoRR Jasmine Bayrooti, Weiwei Kong, Natalia Ponomareva, Carlos Esteves, Ameesh Makadia, Amanda Prorok
2026	J	`jnl`	Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data. CoRR Lucas Rosenblatt, Peihan Liu, Ryan McKenna, Natalia Ponomareva
2025	—	`conf`	A unified framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. CPAL Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder
2025	J	`jnl`	An Optimization Framework for Differentially Private Sparse Fine-Tuning. CoRR Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Hussein Hazimeh, Rahul Mazumder
2025	J	`jnl`	Clustering and Median Aggregation Improve Differentially Private Inference. CoRR Kareem Amin, Salman Avestimehr, Sara Babakniya, Alex Bie, Weiwei Kong, Natalia Ponomareva, Umar Syed
2025	—	`conf`	DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation. SaTML Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora
2025	J	`jnl`	HASSLE-free: A unified Framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. CoRR Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder
2025	J	`jnl`	How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy. CoRR Natalia Ponomareva, Zheng Xu, H. Brendan McMahan, Peter Kairouz, Lucas Rosenblatt, Vincent Cohen-Addad, Cristóbal Guzmán, Ryan McKenna, Galen Andrew, Alex Bie, Da Yu, Alex Kurakin, Morteza Zadimoghaddam, Sergei Vassilvitskii, Andreas Terzis
2025	—	`conf`	SPARTA: An Optimization Framework for Differentially Private Sparse Fine-Tuning. KDD (2) Mehdi Makni, Kayhan Behdin, Gabriel Afriat, Zheng Xu, Sergei Vassilvitskii, Natalia Ponomareva, Rahul Mazumder, Hussein Hazimeh
2025	A*	`conf`	Scaling Laws for Downstream Task Performance in Machine Translation. ICLR Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo
2024	J	`jnl`	DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation. CoRR Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora
2024	A*	`conf`	OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. ICML Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder
2024	J	`jnl`	OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. CoRR Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder
2024	—	`conf`	Private prediction for large-scale synthetic text generation. EMNLP (Findings) Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
2024	J	`jnl`	Private prediction for large-scale synthetic text generation. CoRR Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii
2024	J	`jnl`	Scaling Laws for Downstream Task Performance of Large Language Models. CoRR Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo
2024	—	`conf`	Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models. NAACL-HLT Aldo G. Carranza, Rezsa Farahani, Natalia Ponomareva, Alexey Kurakin, Matthew Jagielski, Milad Nasr
2023	A*	`conf`	COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. KDD Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	J	`jnl`	COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. CoRR Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	J	`jnl`	Explaining and Adapting Graph Conditional Shift. CoRR Qi Zhu, Yizhu Jiao, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
2023	A*	`conf`	Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. ICML Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	J	`jnl`	Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. CoRR Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
2023	J	`jnl`	Harnessing large-language models to generate private synthetic text. CoRR Alexey Kurakin, Natalia Ponomareva, Umar Syed, Liam MacDermed, Andreas Terzis
2023	J	`jnl`	How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. CoRR Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Thakurta
2023	J	`jnl`	How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. J. Artif. Intell. Res. Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Guha Thakurta
2023	A*	`conf`	How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. KDD Natalia Ponomareva, Sergei Vassilvitskii, Zheng Xu, Brendan McMahan, Alexey Kurakin, Chiyaun Zhang
2023	A	`conf`	Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets. AISTATS Hussein Hazimeh, Natalia Ponomareva
2023	J	`jnl`	Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets. CoRR Hussein Hazimeh, Natalia Ponomareva
2023	J	`jnl`	Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models. CoRR Aldo Gael Carranza, Rezsa Farahani, Natalia Ponomareva, Alex Kurakin, Matthew Jagielski, Milad Nasr
2022	—	`conf`	Newer is Not Always Better: Rethinking Transferability Metrics, Their Peculiarities, Stability and Performance. ECML/PKDD (1) Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
2022	—	`conf`	Training Text-to-Text Transformers with Privacy Guarantees. ACL (Findings) Natalia Ponomareva, Jasmijn Bastings, Sergei Vassilvitskii
2021	J	`jnl`	Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance. CoRR Shibal Ibrahim, Natalia Ponomareva, Rahul Mazumder
2021	A*	`conf`	Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data. NeurIPS Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
2021	J	`jnl`	Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data. CoRR Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
2020	A	`conf`	Accelerating Gradient Boosting Machines. AISTATS Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni
2020	A*	`conf`	The Tree Ensemble Layer: Differentiability meets Conditional Computation. ICML Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
2020	J	`jnl`	The Tree Ensemble Layer: Differentiability meets Conditional Computation. CoRR Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
2019	J	`jnl`	Accelerating Gradient Boosting Machine. CoRR Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni
2019	A	`conf`	Agent Prioritization for Autonomous Navigation. IROS Khaled S. Refaat, Kai Ding, Natalia Ponomareva, Stéphane Ross
2019	J	`jnl`	Agent Prioritization for Autonomous Navigation. CoRR Khaled S. Refaat, Kai Ding, Natalia Ponomareva, Stéphane Ross
2017	J	`jnl`	Compact Multi-Class Boosted Trees. CoRR Natalia Ponomareva, Thomas Colthurst, Gilbert Hendry, Salem Haykal, Soroush Radpour
2017	—	`conf`	Compact multi-class boosted trees. IEEE BigData Natalia Ponomareva, Thomas Colthurst, Gilbert Hendry, Salem Haykal, Soroush Radpour
2017	—	`conf`	TF Boosted Trees: A Scalable TensorFlow Based Framework for Gradient Boosting. ECML/PKDD (3) Natalia Ponomareva, Soroush Radpour, Gilbert Hendry, Salem Haykal, Thomas Colthurst, Petr Mitrichev, Alexander Grushetsky
2017	J	`jnl`	TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting. CoRR Natalia Ponomareva, Soroush Radpour, Gilbert Hendry, Salem Haykal, Thomas Colthurst, Petr Mitrichev, Alexander Grushetsky
2017	B	`conf`	Text based user comments as a signal for automatic language identification of online videos. ICMI A. Seza Dogruöz, Natalia Ponomareva, Sertan Girgin, Reshu Jain, Christoph Oehler
2015	C	`conf`	A Classifier for the Latency-CPU Behaviors of Serving Jobs in Distributed Environments. CloudCom Christophe Restif, Natalia Ponomareva, Krzysztof Ostrowski