activity
20142024
most citedLow-Complexity Cloud Image Privacy Protection via Matrix Perturbation

4 citations · 12 across the 16 of their papers we have counts for

collaborators

16 papers

cs.LG2024

The Power of Second Chance: Personalized Submodular Maximization with Two Candidates

Jing Yuan, Shaojie Tang

Most of existing studies on submodular maximization focus on selecting a subset of items that maximizes a \emph{single} submodular function. However, in many real-world scenarios,…

cs.DM2024

A Constant-Approximation Algorithm for Budgeted Sweep Coverage with Mobile Sensors

Wei Liang, Shaojie Tang, Zhao Zhang

In this paper, we present the first constant-approximation algorithm for {\em budgeted sweep coverage problem} (BSC). The BSC involves designing routes for a number of mobile senso…

cs.LG20241 cited

The Diversity Bonus: Learning from Dissimilar Distributed Clients in Personalized Federated Learning

Xinghao Wu, Xuefeng Liu, Jianwei Niu +4

Personalized Federated Learning (PFL) is a commonly used framework that allows clients to collaboratively train their personalized models. PFL is particularly useful for handling s…

eess.IV20241 cited

Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA

Shaojie Tang, Penpen Miao, Xingyu Gao +10

A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) a…

cs.DS2023

Data Summarization beyond Monotonicity: Non-monotone Two-Stage Submodular Maximization

Shaojie Tang

The objective of a two-stage submodular maximization problem is to reduce the ground set using provided training functions that are submodular, with the aim of ensuring that optimi…

cs.LG2023

Lifting the Veil: Unlocking the Power of Depth in Q-learning

Shao-Bo Lin, Tao Li, Shaojie Tang +2

With the help of massive data and rich computational resources, deep Q-learning has been widely used in operations research and management science and has contributed to great succ…