Backurs, Arturs

18 publications

COLT 2025 DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan Kulkarni, Thomas Rothvoss, Sivakanth Gopi

NeurIPS 2025 Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Shuaiqi Wang, Vikas Raunak, Arturs Backurs, Victor Reis, Pei Zhou, Sihao Chen, Longqi Yang, Zinan Lin, Sergey Yekhanin, Giulia Fanti

ICML 2024 Differentially Private Synthetic Data via Foundation Model APIs 2: Text Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin

ICLRW 2024 Differentially Private Synthetic Data via Foundation Model APIs 2: Text Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin

ICLR 2024 Efficiently Computing Similarities to Private Datasets Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski

ICLR 2024 Privately Aligning Language Models with Reinforcement Learning Fan Wu, Huseyin A Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim

ICLR 2023 Exploring the Limits of Differentially Private Deep Learning with Group-Wise Clipping Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian

NeurIPSW 2023 Training Private and Efficient Language Models with Synthetic Data from LLMs Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang

ICLR 2022 Differentially Private Fine-Tuning of Language Models Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang

NeurIPS 2022 Differentially Private Model Compression FatemehSadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni

ICML 2021 Faster Kernel Matrix Algebra via Density Estimation Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner

COLT 2020 Active Local Learning Arturs Backurs, Avrim Blum, Neha Gupta

NeurIPS 2020 Impossibility Results for Grammar-Compressed Linear Algebra Amir Abboud, Arturs Backurs, Karl Bringmann, Marvin Künnemann

ICML 2020 Scalable Nearest Neighbor Search for Optimal Transport Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner

ICML 2019 Scalable Fair Clustering Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner

NeurIPS 2019 Space and Time Efficient Kernel Density Estimation in High Dimensions Arturs Backurs, Piotr Indyk, Tal Wagner

ICML 2017 Improving Viterbi Is Hard: Better Runtimes Imply Faster Clique Algorithms Arturs Backurs, Christos Tzamos

NeurIPS 2017 On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks Arturs Backurs, Piotr Indyk, Ludwig Schmidt