80 citations · 189 across the 36 of their papers we have counts for
38 papers
On the Convergence Rate Lower Bound of Biochemical Computational Modules
Yuzhen Fan, Chuanhou Gao, Shibo He +1
Biochemical reaction networks have become a central theoretical framework for implementing molecular computation. A key challenge is finite time computational accuracy, as computat…
PrivATE: Differentially Private Average Treatment Effect Estimation for Observational Data
Quan Yuan, Xiaochen Li, Linkang Du +6
Causal inference plays a crucial role in scientific research across multiple disciplines. Estimating causal effects, particularly the average treatment effect (ATE), from observati…
VICTOR: Dataset Copyright Auditing in Video Recognition Systems
Quan Yuan, Zhikun Zhang, Linkang Du +5
Video recognition systems are increasingly being deployed in daily life, such as content recommendation and security monitoring. To enhance video recognition development, many inst…
Transformability reveals the interplay of dynamics across different network orders
Ming Xie, Shibo He, Aming Li +3
Recent studies have investigated various dynamic processes characterizing collective behaviors in real-world systems. However, these dynamics have been studied individually in spec…
PSGraph: Differentially Private Streaming Graph Synthesis by Considering Temporal Dynamics
Quan Yuan, Zhikun Zhang, Linkang Du +6
Streaming graphs are ubiquitous in daily life, such as evolving social networks and dynamic communication systems. Due to the sensitive information contained in the graph, directly…
FairDD: Fair Dataset Distillation
Qihang Zhou, Shenhao Fang, Shibo He +2
Condensing large datasets into smaller synthetic counterparts has demonstrated its promise for image classification. However, previous research has overlooked a crucial concern in…
Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey
Kun Shi, Shibo He, Zhenyu Shi +4
Multi-modal fusion is imperative to the implementation of reliable object detection and tracking in complex environments. Exploiting the synergy of heterogeneous modal information…
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection
Qihang Zhou, Jiangtao Yan, Shibo He +2
Zero-shot (ZS) 3D anomaly detection is a crucial yet unexplored field that addresses scenarios where target 3D training samples are unavailable due to practical concerns like priva…
GesturePrint: Enabling User Identification for mmWave-based Gesture Recognition Systems
Lilin Xu, Keyi Wang, Chaojie Gu +3
The millimeter-wave (mmWave) radar has been exploited for gesture recognition. However, existing mmWave-based gesture recognition methods cannot identify different users, which is…
MESEN: Exploit Multimodal Data to Design Unimodal Human Activity Recognition with Few Labels
Lilin Xu, Chaojie Gu, Rui Tan +2
Human activity recognition (HAR) will be an essential function of various emerging applications. However, HAR typically encounters challenges related to modality limitations and la…
Deep Learning Enabled Semantic Communication Systems for Video Transmission
Zhenguo Zhang, Qianqian Yang, Shibo He +1
Semantic communication has emerged as a promising approach for improving efficient transmission in the next generation of wireless networks. Inspired by the success of semantic com…
Label-Free Multivariate Time Series Anomaly Detection
Qihang Zhou, Shibo He, Haoyu Liu +2
Anomaly detection in multivariate time series (MTS) has been widely studied in one-class classification (OCC) setting. The training samples in OCC are assumed to be normal, which i…
Confidant: Customizing Transformer-based LLMs via Collaborative Edge Training
Yuhao Chen, Yuxuan Yan, Qianqian Yang +3
Transformer-based large language models (LLMs) have demonstrated impressive capabilities in a variety of natural language processing (NLP) tasks. Nonetheless, it is challenging to…
AccEPT: An Acceleration Scheme for Speeding Up Edge Pipeline-parallel Training
Yuhao Chen, Yuxuan Yan, Qianqian Yang +4
It is usually infeasible to fit and train an entire large deep neural network (DNN) model using a single edge device due to the limited resources. To facilitate intelligent applica…
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection
Qihang Zhou, Guansong Pang, Yu Tian +2
Zero-shot anomaly detection (ZSAD) requires detection models trained using auxiliary data to detect anomalies without any training sample in a target dataset. It is a crucial task…
Robust Fully-Asynchronous Methods for Distributed Training over General Architecture
Zehan Zhu, Ye Tian, Yan Huang +2
Perfect synchronization in distributed machine learning problems is inefficient and even impossible due to the existence of latency, package losses and stragglers. We propose a Rob…
DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling
Bicheng Guo, Shuxuan Guo, Miaojing Shi +4
Differentiable architecture search (DARTS) has been a mainstream direction in automatic machine learning. Since the discovery that original DARTS will inevitably converge to poor a…
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model
Haiming Wang, Zhikun Zhang, Tianhao Wang +4
Publishing trajectory data (individual's movement information) is very useful, but it also raises privacy concerns. To handle the privacy concern, in this paper, we apply different…
Efficient View Path Planning for Autonomous Implicit Reconstruction
Jing Zeng, Yanxu Li, Yunlong Ran +6
Implicit neural representations have shown promising potential for the 3D scene reconstruction. Recent work applies it to autonomous 3D reconstruction by learning information gain…
Detecting Multivariate Time Series Anomalies with Zero Known Label
Qihang Zhou, Jiming Chen, Haoyu Liu +2
Multivariate time series anomaly detection has been extensively studied under the semi-supervised setting, where a training dataset with all normal instances is required. However,…
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations
Yunlong Ran, Jing Zeng, Shibo He +5
Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying t…
AsyncFedED: Asynchronous Federated Learning with Euclidean Distance based Adaptive Weight Aggregation
Qiyuan Wang, Qianqian Yang, Shibo He +2
In an asynchronous federated learning framework, the server updates the global model once it receives an update from a client instead of waiting for all the updates to arrive as in…
Semantic-preserved Communication System for Highly Efficient Speech Transmission
Tianxiao Han, Qianqian Yang, Zhiguo Shi +2
Deep learning (DL) based semantic communication methods have been explored for the efficient transmission of images, text, and speech in recent years. In contrast to traditional wi…
Semantic-aware Speech to Text Transmission with Redundancy Removal
Tianxiao Han, Qianqian Yang, Zhiguo Shi +2
Deep learning (DL) based semantic communication methods have been explored for the efficient transmission of images, text, and speech in recent years. In contrast to traditional wi…