Ghazi, Badih

39 publications

AISTATS 2025 Balls-and-Bins Sampling for DP-SGD Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Jacob Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

COLT 2025 PREM: Privately Answering Statistical Queries with Relative Error Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva

NeurIPS 2025 Private Hyperparameter Tuning with Ex-Post Guarantee Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

NeurIPS 2025 Quantifying Cross-Modality Memorization in Vision-Language Models Yuxin Wen, Yangsibo Huang, Tom Goldstein, Ravi Kumar, Badih Ghazi, Chiyuan Zhang

NeurIPS 2025 Scaling Embedding Layers in Language Models Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang

ICML 2025 Scaling Laws for Differentially Private Language Models Ryan Mckenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang

ICLR 2025 Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang

NeurIPSW 2024 Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang

NeurIPS 2024 Differentially Private Optimization with Sparse Gradients Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

ICML 2024 How Private Are DP-SGD Implementations? Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

ICML 2024 Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

ICLR 2024 LabelDP-Pro: Learning with Label Differential Privacy via Projections Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

COLT 2024 On Convex Optimization with Semi-Sensitive Features Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPSW 2024 On Memorization of Large Language Models in Logical Reasoning Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar

NeurIPS 2024 Scalable DP-SGD: Shuffling vs. Poisson Subsampling Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

AAAI 2023 Differentially Private Heatmaps Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan

NeurIPS 2023 On Computing Pairwise Statistics with Local Differential Privacy Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

NeurIPS 2023 On Differentially Private Sampling from Gaussian and Product Distributions Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi

ICML 2023 On User-Level Private Convex Optimization Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPS 2023 Optimal Unbiased Randomizers for Regression with Label Differential Privacy Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang

ICLR 2023 Regression with Label Differential Privacy Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang

NeurIPS 2023 Sparsity-Preserving Differentially Private Training of Large Embedding Models Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

COLT 2023 Ticketed Learning–Unlearning Schemes Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang

NeurIPS 2023 User-Level Differential Privacy with Few Examples per User Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

NeurIPS 2022 Anonymized Histograms in Intermediate Privacy Models Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

ICML 2022 Faster Privacy Accounting via Evolving Discretization Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

NeurIPS 2022 Private Isotonic Regression Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

AAAI 2022 Private Rank Aggregation in Central and Local Models Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi

AISTATS 2021 Robust and Private Learning of Halfspaces Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen

FnTML 2021 Advances and Open Problems in Federated Learning Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

NeurIPS 2021 Deep Learning with Label Differential Privacy Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

ICML 2021 Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha

ICML 2021 Locally Private K-Means in One Round Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi

ALT 2021 Near-Tight Closure Bounds for the Littlestone and Threshold Dimensions Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi

COLT 2021 On Avoiding the Union Bound When Answering Multiple Differentially Private Queries Badih Ghazi, Ravi Kumar, Pasin Manurangsi

NeurIPS 2021 User-Level Differentially Private Learning via Correlated Sampling Badih Ghazi, Ravi Kumar, Pasin Manurangsi

NeurIPS 2020 Differentially Private Clustering: Tight Approximation Ratios Badih Ghazi, Ravi Kumar, Pasin Manurangsi

ICML 2020 Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh

ICML 2019 Recursive Sketches for Modular Deep Learning Badih Ghazi, Rina Panigrahy, Joshua Wang