activity
20132024
most citedSmartLoc: Sensing Landmarks Silently for Smartphone Based Metropolitan Localization

2 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2024

DeepCore: Simple Fingerprint Construction for Differentiating Homologous and Piracy Models

Haifeng Sun, Lan Zhang, Xiang-Yang Li

As intellectual property rights, the copyright protection of deep models is becoming increasingly important. Existing work has made many attempts at model watermarking and fingerpr…

cs.CR2023★ 1 cited

Secure Transformer Inference Protocol

Mu Yuan, Lan Zhang, Xiang-Yang Li

Security of model parameters and user data is critical for Transformer-based services, such as ChatGPT. While recent strides in secure two-party protocols have successfully address…

cs.LG2023★ 1 cited

Tight Memory-Regret Lower Bounds for Streaming Bandits

Shaoang Li, Lan Zhang, Junhao Wang +1

In this paper, we investigate the streaming bandits problem, wherein the learner aims to minimize regret by dealing with online arriving arms and sublinear arm memory. We establish…

cs.CR2023

TPMDP: Threshold Personalized Multi-party Differential Privacy via Optimal Gaussian Mechanism

Jiandong Liu, Lan Zhang, Chaojie Lv +3

In modern distributed computing applications, such as federated learning and AIoT systems, protecting privacy is crucial to prevent adversarial parties from colluding to steal othe…

cs.LG2022★ 1 cited

Data Origin Inference in Machine Learning

Mingxue Xu, Xiang-Yang Li

It is a growing direction to utilize unintended memorization in ML models to benefit real-world applications, with recent efforts like user auditing, dataset ownership inference an…

cs.AI2022

MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference

Mu Yuan, Lan Zhang, Zimu Zheng +2

The cost efficiency of model inference is critical to real-world machine learning (ML) applications, especially for delay-sensitive tasks and resource-limited devices. A typical di…

cs.AI2022

InFi: End-to-End Learning to Filter Input for Resource-Efficiency in Mobile-Centric Inference

Mu Yuan, Lan Zhang, Fengxiang He +4

Mobile-centric AI applications have high requirements for resource-efficiency of model inference. Input filtering is a promising approach to eliminate the redundancy so as to reduc…

cs.NI2013★ 2 cited

SmartLoc: Sensing Landmarks Silently for Smartphone Based Metropolitan Localization

Cheng Bo, Xiang-Yang Li, Taeho Jung +1

We present \emph{SmartLoc}, a localization system to estimate the location and the traveling distance by leveraging the lower-power inertial sensors embedded in smartphones as a su…