99 citations · 118 across the 14 of their papers we have counts for
14 papers
1st Place Solution for the 5th LSVOS Challenge: Video Instance Segmentation
Tao Zhang, Xingye Tian, Yikang Zhou +7
Video instance segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. In this report…
Comprehensive Analysis of Network Robustness Evaluation Based on Convolutional Neural Networks with Spatial Pyramid Pooling
Wenjun Jiang, Tianlong Fan, Changhao Li +3
Connectivity robustness, a crucial aspect for understanding, optimizing, and repairing complex networks, has traditionally been evaluated through time-consuming and often impractic…
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off
Huiqiang Chen, Tianqing Zhu, Tao Zhang +2
Federated learning (FL) has been a hot topic in recent years. Ever since it was introduced, researchers have endeavored to devise FL systems that protect privacy or ensure fair res…
Semi-Supervised Federated Learning for Keyword Spotting
Enmao Diao, Eric W. Tramel, Jie Ding +1
Keyword Spotting (KWS) is a critical aspect of audio-based applications on mobile devices and virtual assistants. Recent developments in Federated Learning (FL) have significantly…
Do Pre-trained Language Models Indeed Understand Software Engineering Tasks?
Yao Li, Tao Zhang, Xiapu Luo +3
Artificial intelligence (AI) for software engineering (SE) tasks has recently achieved promising performance. In this paper, we investigate to what extent the pre-trained language…
Federated Learning with Server Learning: Enhancing Performance for Non-IID Data
Van Sy Mai, Richard J. La, Tao Zhang
Federated Learning (FL) has emerged as a means of distributed learning using local data stored at clients with a coordinating server. Recent studies showed that FL can suffer from…
Self-Aware Personalized Federated Learning
Huili Chen, Jie Ding, Eric Tramel +4
In the context of personalized federated learning (FL), the critical challenge is to balance local model improvement and global model tuning when the personal and global objectives…
Federated Learning Challenges and Opportunities: An Outlook
Jie Ding, Eric Tramel, Anit Kumar Sahu +3
Federated learning (FL) has been developed as a promising framework to leverage the resources of edge devices, enhance customers' privacy, comply with regulations, and reduce devel…
Geo-MOEA: A Multi-Objective Evolutionary Algorithm with Geo-obfuscation for Mobile Crowdsourcing Workers
Shun Zhang, Tao Zhang, Zhili Chen +1
The rapid development of mobile Internet and sharing economy brings the prosperity of Spatial Crowdsourcing (SC). SC applications assign various tasks according to reported locatio…
Correlated Differential Privacy: Feature Selection in Machine Learning
Tao Zhang, Tianqing Zhu, Ping Xiong +3
Privacy preserving in machine learning is a crucial issue in industry informatics since data used for training in industries usually contain sensitive information. Existing differe…
Fairness Constraints in Semi-supervised Learning
Tao Zhang, Tianqing Zhu, Mengde Han +3
Fairness in machine learning has received considerable attention. However, most studies on fair learning focus on either supervised learning or unsupervised learning. Very few cons…
Correlated Data in Differential Privacy: Definition and Analysis
Tao Zhang, Tianqing Zhu, Renping Liu +1
Differential privacy is a rigorous mathematical framework for evaluating and protecting data privacy. In most existing studies, there is a vulnerable assumption that records in a d…
Feature Location Benchmark for Decomposing and Reusing Android Apps
Yutian Tang, Hao Zhou, Zhou Xu +3
Software reuse enables developers to reuse architecture, programs and other software artifacts. Realizing a systematical reuse in software brings a large amount of benefits for sta…
DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
Ao Ren, Tao Zhang, Yuhao Wang +5
The rapidly growing parameter volume of deep neural networks (DNNs) hinders the artificial intelligence applications on resource constrained devices, such as mobile and wearable de…