Xin Lyu

PhD student, University of California, Berkeley

Joined

May 2022

Names

Xin Lyu (Preferred)

Emails

****@berkeley.edu (Confirmed)

****@gmail.com (Confirmed)

Personal Links

Homepage

Career & Education History

PhD student

University of California, Berkeley (berkeley.edu)

2021 – 2026

Undergrad student

Tsinghua University, Tsinghua University (tsinghua.edu.cn)

2017 – 2021

Advisors, Relations & Conflicts

No relations added

Expertise

Computational Complexity

Present

Differential Privacy

2021 – Present

Publications

Hot PATE: Private Aggregation of Distributions for Diverse Tasks
Edith Cohen, Benjamin Cohen-Wang, Xin Lyu, Jelani Nelson, Tamas Sarlos, Uri Stemmer
- ICLR 2026 Poster
- Readers: Everyone
Trade-offs in Data Memorization via Strong Data Processing Inequalities
Vitaly Feldman, Guy Kornowski, Xin Lyu
- MemFM
- Readers: Everyone
Hot PATE: Private Aggregation of Distributions for Diverse Tasks
Edith Cohen, Benjamin Cohen-Wang, Xin Lyu, Jelani Nelson, Tamas Sarlos, Uri Stemmer
- Submitted to ICML 2025
- Readers: Everyone
Hot PATE: Private Aggregation of Distributions for Diverse Tasks
Edith Cohen, Benjamin Cohen-Wang, Xin Lyu, Jelani Nelson, Tamas Sarlos, Uri Stemmer
- Submitted to ICLR 2025
- Readers: Everyone
Hot PATE: Private Aggregation of Distributions for Diverse Tasks
Edith Cohen, Xin Lyu, Jelani Nelson, Tamas Sarlos, Uri Stemmer
- Submitted to ICLR 2024
- Readers: Everyone
The Target-Charging Technique for Privacy Analysis across Interactive Computations
Edith Cohen, Xin Lyu
- NeurIPS 2023 poster
- Readers: Everyone
Generalized Private Selection and Testing with High Confidence
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
- 2023 (modified: 16 Apr 2023)
- ITCS 2023
- Readers: Everyone
The Target-Charging Technique for Privacy Accounting across Interactive Computations
Edith Cohen, Xin Lyu
- 2023 (modified: 24 Apr 2023)
- CoRR 2023
- Readers: Everyone
Composition Theorems for Interactive Differential Privacy
Xin Lyu
- Published: 31 Oct 2022, Last Modified: 11 Jan 2023
- NeurIPS 2022 Accept
- Readers: Everyone
On the Robustness of CountSketch to Adaptive Inputs
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
- 2022 (modified: 16 Apr 2023)
- ICML 2022
- Readers: Everyone

View all 15 publications