activity
20172026
most citedDifferentially Private Testing of Identity and Closeness of Discrete Distributions

21 citations · 29 across the 5 of their papers we have counts for

collaborators

10 papers

cs.LG2026

Efficient DP-SGD for LLMs with Randomized Clipping

Enayat Ullah, Sai Aparna Aketi, Devansh Gupta +2

Large language models (LLMs) are trained on vast datasets that may contain sensitive information. Differential privacy (DP), the de facto standard for formal privacy guarantees, pr…

cs.DS20212 cited

Statistical Inference in the Differential Privacy Model

Huanyu Zhang

In modern settings of data analysis, we may be running our algorithms on datasets that are sensitive in nature. However, classical machine learning and statistical algorithms were…

cs.IT20214 cited

Robust Testing and Estimation under Manipulation Attacks

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

We study robust testing and estimation of discrete distributions in the strong contamination model. We consider both the "centralized setting" and the "distributed setting with inf…

cs.LG2021

Wide Network Learning with Differential Privacy

Huanyu Zhang, Ilya Mironov, Meisam Hejazinia

Despite intense interest and considerable effort, the current generation of neural networks suffers a significant loss of accuracy under most practically relevant privacy training…

eess.SP20212 cited

Joint Design of Transmit Waveforms and Receive Filters for MIMO Radar via Manifold Optimization

Huanyu Zhang, Ziping Zhao

The problem of joint design of transmit waveforms and receive filters is desirable in many application scenarios of multiple-input multiple-output (MIMO) radar systems. In this pap…

cs.LG2020

Differentially Private Assouad, Fano, and Le Cam

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Le Cam's method, Fano's inequality, and Assouad's lemma are three widely used techniques to prove lower bounds for statistical estimation tasks. We propose their analogues under ce…