Ziteng Sun

According to our database, Ziteng Sun authored at least 35 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Private federated discovery of out-of-vocabulary words for Gboard.

Ziteng Sun, Peter Kairouz, Haicheng Sun, Adrià Gascón, Ananda Theertha Suresh

CoRR, 2024

Optimal Block-Level Draft Verification for Accelerating Speculative Decoding.

Ziteng Sun, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh

CoRR, 2024

Asymptotics of Language Model Alignment.

Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh, Ahmad Beirami

Proceedings of the IEEE International Symposium on Information Theory, 2024

The importance of feature preprocessing for differentially private linear optimization.

Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

SpecTr: Fast Speculative Decoding via Optimal Transport.

Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints.

Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Concentration Bounds for Discrete Distribution Estimation in KL Divergence.

Clément L. Canonne, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2023

Federated Heavy Hitter Recovery under Linear Sketching.

Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the International Conference on Machine Learning, 2023

Subset-Based Instance Optimality in Private Estimation.

Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the International Conference on Machine Learning, 2023

User-level Private Stochastic Convex Optimization with Optimal Rates.

Raef Bassily, Ziteng Sun

Proceedings of the International Conference on Machine Learning, 2023

Discrete Distribution Estimation under User-level Local Differential Privacy.

Jayadev Acharya, Yuhan Liu, Ziteng Sun

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Sample Complexity of Distinguishing Cause from Effect.

Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Interactive Inference Under Information Constraints.

Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2022

Correlated Quantization for Distributed Mean Estimation and Optimization.

Ananda Theertha Suresh, Ziteng Sun, Jae Ro, Felix X. Yu

Proceedings of the International Conference on Machine Learning, 2022

The Role of Interactivity in Structured Estimation.

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi, Ziteng Sun

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Inference Under Information Constraints III: Local Privacy Constraints.

Jayadev Acharya, Clément L. Canonne, Cody Freitag, Ziteng Sun, Himanshu Tyagi

IEEE J. Sel. Areas Inf. Theory, 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

Found. Trends Mach. Learn., 2021

Learning with User-Level Privacy.

Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition.

Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, Himanshu Tyagi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robust Testing and Estimation under Manipulation Attacks.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

Differentially Private Assouad, Fano, and Le Cam.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the Algorithmic Learning Theory, 2021

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints.

Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun

Proceedings of the Algorithmic Learning Theory, 2021

2020

INSPECTRE: Privately Estimating the Unseen.

Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang

J. Priv. Confidentiality, 2020

Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints.

Jayadev Acharya, Yuhan Liu, Ziteng Sun

CoRR, 2020

Context Aware Local Differential Privacy.

Jayadev Acharya, Kallista A. Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit.

Jayadev Acharya, Clément L. Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi

Electron. Colloquium Comput. Complex., 2019

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, 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

CoRR, 2019

Can You Really Backdoor Federated Learning?

Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan

CoRR, 2019

Estimating Entropy of Distributions in Constant Space.

Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters.

Jayadev Acharya, Ziteng Sun

Proceedings of the 36th International Conference on Machine Learning, 2019

Hadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

CoRR, 2018

Differentially Private Testing of Identity and Closeness of Discrete Distributions.

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Improved Bounds for Minimax Risk of Estimating Missing Mass.

Jayadev Acharya, Yelun Bao, Yuheng Kang, Ziteng Sun

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2016

Optimal Byzantine Attack and Byzantine Identification in Distributed Sensor Networks.

Ziteng Sun, Chuang Zhang, Pingyi Fan

Proceedings of the 2016 IEEE Globecom Workshops, Washington, DC, USA, December 4-8, 2016, 2016