Badih Ghazi - RankMe

175 papers A* 45A 12B 3Journal 104Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Computational Hardness of Private Coreset. CoRR Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi
2026	J	`jnl`	Denoising the US Census: Succinct Block Hierarchical Regression. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2025	A	`conf`	Balls-and-Bins Sampling for DP-SGD. AISTATS Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2025	A	`conf`	Differential Privacy on Trust Graphs. ITCS Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Serena Wang
2025	J	`jnl`	How Unique is Whose Web Browser? The role of demographics in browser fingerprinting among US users. Proc. Priv. Enhancing Technol. Alex Berke, Badih Ghazi, Enrico Bacis, Pritish Kamath, Ravi Kumar, Robin Lassonde, Pasin Manurangsi, Umar Syed
2025	J	`jnl`	Linear-Time User-Level DP-SCO via Robust Statistics. CoRR Badih Ghazi, Ravi Kumar, Daogao Liu, Pasin Manurangsi
2025	—	`conf`	On Memorization of Large Language Models in Logical Reasoning. IJCNLP-AACL (long papers) Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar
2025	J	`jnl`	On the Differential Privacy and Interactivity of Privacy Sandbox Reports. Proc. Priv. Enhancing Technol. Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Mariana Raykova, Vikas Sahu, Phillipp Schoppmann
2025	A*	`conf`	PREM: Privately Answering Statistical Queries with Relative Error. COLT Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva
2025	J	`jnl`	PREM: Privately Answering Statistical Queries with Relative Error. CoRR Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva
2025	J	`jnl`	Private Hyperparameter Tuning with Ex-Post Guarantee. CoRR Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2025	J	`jnl`	Quantifying Cross-Modality Memorization in Vision-Language Models. CoRR Yuxin Wen, Yangsibo Huang, Tom Goldstein, Ravi Kumar, Badih Ghazi, Chiyuan Zhang
2025	J	`jnl`	Scaling Embedding Layers in Language Models. CoRR Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang
2025	A*	`conf`	Scaling Laws for Differentially Private Language Models. ICML 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
2025	J	`jnl`	Scaling Laws for Differentially Private Language Models. CoRR 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
2025	A*	`conf`	Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. ICLR Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang
2025	J	`jnl`	Urania: Differentially Private Insights into AI Use. CoRR Daogao Liu, Edith Cohen, Badih Ghazi, Peter Kairouz, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Da Yu, Chiyuan Zhang
2025	J	`jnl`	VaultGemma: A Differentially Private Gemma Model. CoRR Amer Sinha, Thomas Mesnard, Ryan McKenna, Daogao Liu, Christopher A. Choquette-Choo, Yangsibo Huang, Da Yu, Georgios Kaissis, Zachary Charles, Ruibo Liu, Lynn Chua, Pritish Kamath, Pasin Manurangsi, Steve He, Chiyuan Zhang, Badih Ghazi, Borja de Balle Pigem, Prem Eruvbetine, Tris Warkentin, Armand Joulin, Ravi Kumar
2024	J	`jnl`	Balls-and-Bins Sampling for DP-SGD. CoRR Lynn Chua, Badih Ghazi, Charlie Harrison, Ethan Leeman, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang
2024	J	`jnl`	Differential Privacy on Trust Graphs. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Serena Wang
2024	J	`jnl`	Differentially Private Ad Conversion Measurement. CoRR John Delaney, Badih Ghazi, Charlie Harrison, Christina Ilvento, Ravi Kumar, Pasin Manurangsi, Martin Pal, Karthik Prabhakar, Mariana Raykova
2024	J	`jnl`	Differentially Private Ad Conversion Measurement. Proc. Priv. Enhancing Technol. John Delaney, Badih Ghazi, Charlie Harrison, Christina Ilvento, Ravi Kumar, Pasin Manurangsi, Martin Pál, Karthik Prabhakar, Mariana Raykova
2024	A*	`conf`	Differentially Private Optimization with Sparse Gradients. NeurIPS Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2024	J	`jnl`	Differentially Private Optimization with Sparse Gradients. CoRR Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2024	A*	`conf`	How Private are DP-SGD Implementations? ICML Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	How Private is DP-SGD? CoRR Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	How Unique is Whose Web Browser? The role of demographics in browser fingerprinting among US users. CoRR Alex Berke, Enrico Bacis, Badih Ghazi, Pritish Kamath, Ravi Kumar, Robin Lassonde, Pasin Manurangsi, Umar Syed
2024	A*	`conf`	Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2024	J	`jnl`	Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2024	A*	`conf`	LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2024	J	`jnl`	Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	On Computing Pairwise Statistics with Local Differential Privacy. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2024	A*	`conf`	On Convex Optimization with Semi-Sensitive Features. COLT Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2024	J	`jnl`	On Convex Optimization with Semi-Sensitive Features. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2024	J	`jnl`	On Memorization of Large Language Models in Logical Reasoning. CoRR Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar
2024	J	`jnl`	On the Differential Privacy and Interactivity of Privacy Sandbox Reports. CoRR Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, S. Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Vikas Sahu
2024	—	`conf`	Privacy in Web Advertising: Analytics and Modeling. WWW (Companion Volume) Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2024	A	`conf`	Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient. ITC Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2024	A*	`conf`	Scalable DP-SGD: Shuffling vs. Poisson Subsampling. NeurIPS Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Scalable DP-SGD: Shuffling vs. Poisson Subsampling. CoRR Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. Proc. Priv. Enhancing Technol. Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan
2024	—	`conf`	Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. AdKDD@KDD Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Nicolas Mayoraz, Hema Venkata Krishna Giri Narra, Steffen Rendle, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2024	J	`jnl`	Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. CoRR Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2024	J	`jnl`	Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. CoRR Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang
2023	A	`conf`	Algorithms with More Granular Differential Privacy Guarantees. ITCS Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke
2023	A	`conf`	Differentially Private Aggregation via Imperfect Shuffling. ITC Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
2023	J	`jnl`	Differentially Private Aggregation via Imperfect Shuffling. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
2023	A*	`conf`	Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. SODA Justin Y. Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Shyam Narayanan, Jelani Nelson, Yinzhan Xu
2023	A*	`conf`	Differentially Private Data Release over Multiple Tables. PODS Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
2023	J	`jnl`	Differentially Private Data Release over Multiple Tables. CoRR Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	Differentially Private Heatmaps. AAAI Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan
2023	A*	`conf`	On Computing Pairwise Statistics with Local Differential Privacy. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2023	A*	`conf`	On Differentially Private Counting on Trees. ICALP Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu
2023	A*	`conf`	On Differentially Private Sampling from Gaussian and Product Distributions. NeurIPS Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
2023	J	`jnl`	On Differentially Private Sampling from Gaussian and Product Distributions. CoRR Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	On User-Level Private Convex Optimization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2023	J	`jnl`	On User-Level Private Convex Optimization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang
2023	A*	`conf`	Optimal Unbiased Randomizers for Regression with Label Differential Privacy. NeurIPS Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	J	`jnl`	Optimal Unbiased Randomizers for Regression with Label Differential Privacy. CoRR Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	—	`conf`	Optimizing Hierarchical Queries for the Attribution Reporting API. AdKDD@KDD Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu
2023	J	`jnl`	Optimizing Hierarchical Queries for the Attribution Reporting API. CoRR Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu
2023	A*	`conf`	Privacy in Advertising: Analytics and Modeling. KDD Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2023	—	`conf`	Private Ad Modeling with DP-SGD. AdKDD@KDD Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2023	A	`conf`	Private Counting of Distinct and k-Occurring Items in Time Windows. ITCS Badih Ghazi, Ravi Kumar, Jelani Nelson, Pasin Manurangsi
2023	J	`jnl`	Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	Regression with Label Differential Privacy. ICLR Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	J	`jnl`	Separating Computational and Statistical Differential Privacy (Under Plausible Assumptions). CoRR Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2023	J	`jnl`	Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2023	J	`jnl`	Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. CoRR Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan
2023	A*	`conf`	Ticketed Learning-Unlearning Schemes. COLT Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
2023	J	`jnl`	Ticketed Learning-Unlearning Schemes. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
2023	A*	`conf`	Towards Separating Computational and Statistical Differential Privacy. FOCS Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	User-Level Differential Privacy With Few Examples Per User. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2023	J	`jnl`	User-Level Differential Privacy With Few Examples Per User. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2022	J	`jnl`	Algorithms with More Granular Differential Privacy Guarantees. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke
2022	A*	`conf`	Anonymized Histograms in Intermediate Privacy Models. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Anonymized Histograms in Intermediate Privacy Models. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. CoRR Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. Proc. Priv. Enhancing Technol. Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson
2022	J	`jnl`	Differentially Private Heatmaps. CoRR Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi, Vidhya Navalpakkam, Nachiappan Valliappan
2022	A*	`conf`	Distributed, Private, Sparse Histograms in the Two-Server Model. CCS James Bell, Adrià Gascón, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Mariana Raykova, Phillipp Schoppmann
2022	J	`jnl`	Distributed, Private, Sparse Histograms in the Two-Server Model. IACR Cryptol. ePrint Arch. James Bell, Adrià Gascón, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Mariana Raykova, Phillipp Schoppmann
2022	A*	`conf`	Faster Privacy Accounting via Evolving Discretization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Faster Privacy Accounting via Evolving Discretization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	—	`conf`	Large-Scale Differentially Private BERT. EMNLP (Findings) Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Multiparty Reach and Frequency Histogram: Private, Secure, and Practical. Proc. Priv. Enhancing Technol. Badih Ghazi, Ben Kreuter, Ravi Kumar, Pasin Manurangsi, Jiayu Peng, Evgeny Skvortsov, Yao Wang, Craig Wright
2022	J	`jnl`	On Differentially Private Counting on Trees. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu
2022	J	`jnl`	Private Ad Modeling with DP-SGD. CoRR Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2022	J	`jnl`	Private Aggregation of Trajectories. Proc. Priv. Enhancing Technol. Badih Ghazi, Neel Kamal, Ravi Kumar, Pasin Manurangsi, Annika Zhang
2022	J	`jnl`	Private Counting of Distinct and k-Occurring Items in Time Windows. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson
2022	A*	`conf`	Private Isotonic Regression. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Private Isotonic Regression. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	A*	`conf`	Private Rank Aggregation in Central and Local Models. AAAI Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Regression with Label Differential Privacy. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 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
2021	A*	`conf`	Deep Learning with Label Differential Privacy. NeurIPS Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2021	A*	`conf`	Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. ICML Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha
2021	J	`jnl`	Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha
2021	J	`jnl`	Google COVID-19 Vaccination Search Insights: Anonymization Process Description. CoRR Shailesh Bavadekar, Adam Boulanger, John Davis, Damien Desfontaines, Evgeniy Gabrilovich, Krishna Gadepalli, Badih Ghazi, Tague Griffith, Jai Prakash Gupta, Chaitanya Kamath, Dennis Kraft, Ravi Kumar, Akim Kumok, Yael Mayer, Pasin Manurangsi, Arti Patankar, Irippuge Milinda Perera, Chris Scott, Tomer Shekel, Benjamin Miller, Karen Smith, Charlotte Stanton, Mimi Sun, Mark Young, Gregory Wellenius
2021	J	`jnl`	Large-Scale Differentially Private BERT. CoRR Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi
2021	A*	`conf`	Locally Private k-Means in One Round. ICML Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2021	J	`jnl`	Locally Private k-Means in One Round. CoRR Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2021	B	`conf`	Near-tight closure b ounds for the Littlestone and threshold dimensions. ALT Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
2021	A*	`conf`	On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. COLT Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2021	J	`jnl`	On Deep Learning with Label Differential Privacy. CoRR Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2021	A	`conf`	On Distributed Differential Privacy and Counting Distinct Elements. ITCS Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2021	—	`conf`	On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy. EUROCRYPT (3) Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker
2021	J	`jnl`	Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh
2021	J	`jnl`	Private Rank Aggregation in Central and Local Models. CoRR Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2021	A	`conf`	Robust and Private Learning of Halfspaces. AISTATS Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen
2021	A*	`conf`	Sample-efficient proper PAC learning with approximate differential privacy. STOC Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
2021	A*	`conf`	User-Level Differentially Private Learning via Correlated Sampling. NeurIPS Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2021	J	`jnl`	User-Level Private Learning via Correlated Sampling. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2020	A*	`conf`	Differentially Private Clustering: Tight Approximation Ratios. NeurIPS Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2020	J	`jnl`	Differentially Private Clustering: Tight Approximation Ratios. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2020	J	`jnl`	Near-tight closure bounds for Littlestone and threshold dimensions. CoRR Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
2020	J	`jnl`	On Avoiding the Union Bound When Answering Multiple Differentially Private Queries. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2020	J	`jnl`	On Distributed Differential Privacy and Counting Distinct Elements. CoRR Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2020	J	`jnl`	Optimality of Correlated Sampling Strategies. Theory Comput. Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan
2020	—	`conf`	Private Aggregation from Fewer Anonymous Messages. EUROCRYPT (2) Badih Ghazi, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker
2020	A*	`conf`	Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead. ICML Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh
2020	A	`conf`	Pure Differentially Private Summation from Anonymous Messages. ITC Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker
2020	J	`jnl`	Pure Differentially Private Summation from Anonymous Messages. CoRR Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker
2020	J	`jnl`	Robust and Private Learning of Halfspaces. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen
2020	J	`jnl`	Sample-efficient proper PAC learning with approximate differential privacy. CoRR Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR 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, 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, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, 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
2019	A*	`conf`	Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. SODA Madhu Sudan, Badih Ghazi, Noah Golowich, Mitali Bafna
2019	J	`jnl`	On the Power of Multiple Anonymous Messages. IACR Cryptol. ePrint Arch. Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker
2019	J	`jnl`	Private Aggregation from Fewer Anonymous Messages. CoRR Badih Ghazi, Pasin Manurangsi, Rasmus Pagh, Ameya Velingker
2019	J	`jnl`	Private Heavy Hitters and Range Queries in the Shuffled Model. CoRR Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker
2019	A*	`conf`	Recursive Sketches for Modular Deep Learning. ICML Badih Ghazi, Rina Panigrahy, Joshua R. Wang
2019	J	`jnl`	Recursive Sketches for Modular Deep Learning. CoRR Badih Ghazi, Rina Panigrahy, Joshua R. Wang
2019	J	`jnl`	Scalable and Differentially Private Distributed Aggregation in the Shuffled Model. CoRR Badih Ghazi, Rasmus Pagh, Ameya Velingker
2018	J	`jnl`	Communication with Contextual Uncertainty. Comput. Complex. Badih Ghazi, Ilan Komargodski, Pravesh K. Kothari, Madhu Sudan
2018	J	`jnl`	Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. CoRR Mitali Bafna, Badih Ghazi, Noah Golowich, Madhu Sudan
2018	J	`jnl`	Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation. Electron. Colloquium Comput. Complex. Mitali Bafna, Badih Ghazi, Noah Golowich, Madhu Sudan
2018	—	`—`	Computational aspects of communication amid uncertainty. Badih Ghazi
2018	A	`conf`	Dimension Reduction for Polynomials over Gaussian Space and Applications. CCC Badih Ghazi, Pritish Kamath, Prasad Raghavendra
2018	J	`jnl`	LP/SDP Hierarchy Lower Bounds for Decoding Random LDPC Codes. IEEE Trans. Inf. Theory Badih Ghazi, Euiwoong Lee
2018	J	`jnl`	NP-Hardness of Reed-Solomon Decoding, and the Prouhet-Tarry-Escott Problem. SIAM J. Comput. Venkata Gandikota, Badih Ghazi, Elena Grigorescu
2018	A*	`conf`	Resource-Efficient Common Randomness and Secret-Key Schemes. SODA Badih Ghazi, T. S. Jayram
2017	A	`conf`	Compression in a Distributed Setting. ITCS Badih Ghazi, Elad Haramaty, Pritish Kamath, Madhu Sudan
2017	J	`jnl`	Dimension Reduction for Polynomials over Gaussian Space and Applications. CoRR Badih Ghazi, Pritish Kamath, Prasad Raghavendra
2017	J	`jnl`	Dimension Reduction for Polynomials over Gaussian Space and Applications. Electron. Colloquium Comput. Complex. Badih Ghazi, Pritish Kamath, Prasad Raghavendra
2017	A	`conf`	On the Power of Learning from k-Wise Queries. ITCS Vitaly Feldman, Badih Ghazi
2017	J	`jnl`	On the Power of Learning from k-Wise Queries. CoRR Vitaly Feldman, Badih Ghazi
2017	J	`jnl`	Resource-Efficient Common Randomness and Secret-Key Schemes. CoRR Badih Ghazi, T. S. Jayram
2017	J	`jnl`	Resource-Efficient Common Randomness and Secret-Key Schemes. Electron. Colloquium Comput. Complex. Badih Ghazi, T. S. Jayram
2017	A*	`conf`	The Power of Shared Randomness in Uncertain Communication. ICALP Badih Ghazi, Madhu Sudan
2017	J	`jnl`	The Power of Shared Randomness in Uncertain Communication. CoRR Badih Ghazi, Madhu Sudan
2017	J	`jnl`	The Power of Shared Randomness in Uncertain Communication. Electron. Colloquium Comput. Complex. Badih Ghazi, Madhu Sudan
2016	A*	`conf`	Communication Complexity of Permutation-Invariant Functions. SODA Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	A*	`conf`	Communication with Contextual Uncertainty. SODA Badih Ghazi, Ilan Komargodski, Pravesh Kothari, Madhu Sudan
2016	J	`jnl`	Decidability of Non-Interactive Simulation of Joint Distributions. CoRR Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	J	`jnl`	Decidability of Non-Interactive Simulation of Joint Distributions. Electron. Colloquium Comput. Complex. Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	A*	`conf`	Decidability of Non-interactive Simulation of Joint Distributions. FOCS Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	A*	`conf`	NP-Hardness of Reed-Solomon Decoding and the Prouhet-Tarry-Escott Problem. FOCS Venkata Gandikota, Badih Ghazi, Elena Grigorescu
2016	J	`jnl`	NP-Hardness of Reed-Solomon Decoding, and the Prouhet-Tarry-Escott Problem. CoRR Venkata Gandikota, Badih Ghazi, Elena Grigorescu
2016	J	`jnl`	NP-Hardness of Reed-Solomon Decoding, and the Prouhet-Tarry-Escott Problem. Electron. Colloquium Comput. Complex. Venkata Gandikota, Badih Ghazi, Elena Grigorescu
2016	J	`jnl`	The Optimality of Correlated Sampling. CoRR Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan
2016	J	`jnl`	The Optimality of Correlated Sampling. Electron. Colloquium Comput. Complex. Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan
2015	J	`jnl`	Communication Complexity of Permutation-Invariant Functions. CoRR Badih Ghazi, Pritish Kamath, Madhu Sudan
2015	J	`jnl`	Communication Complexity of Permutation-Invariant Functions. Electron. Colloquium Comput. Complex. Badih Ghazi, Pritish Kamath, Madhu Sudan
2015	A*	`conf`	LP/SDP Hierarchy Lower Bounds for Decoding Random LDPC Codes. SODA Badih Ghazi, Euiwoong Lee
2015	B	`conf`	On the NP-hardness of bounded distance decoding of Reed-Solomon codes. ISIT Venkata Gandikota, Badih Ghazi, Elena Grigorescu
2014	J	`jnl`	LP/SDP Hierarchy Lower Bounds for Decoding Random LDPC Codes. CoRR Badih Ghazi, Euiwoong Lee
2014	J	`jnl`	Linear Programming Decoding of Spatially Coupled Codes. IEEE Trans. Inf. Theory Louay Bazzi, Badih Ghazi, Rüdiger L. Urbanke
2014	—	`conf`	The Information Complexity of Hamming Distance. APPROX-RANDOM Eric Blais, Joshua Brody, Badih Ghazi
2013	J	`jnl`	Linear Programming Decoding of Spatially Coupled Codes CoRR Louay Bazzi, Badih Ghazi, Rüdiger L. Urbanke
2013	B	`conf`	Linear programming decoding of spatially coupled codes. ISIT Louay Bazzi, Badih Ghazi, Rüdiger L. Urbanke
2013	J	`jnl`	Sample-Optimal Average-Case Sparse Fourier Transform in Two Dimensions CoRR Badih Ghazi, Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price, Lixin Shi
2013	—	`conf`	Sample-optimal average-case sparse Fourier Transform in two dimensions. Allerton Badih Ghazi, Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price, Lixin Shi