b'Kai Zhou'

research

∙ 09/05/2023

Black-Box Attacks against Signed Graph Analysis via Balance Poisoning

Signed graphs are well-suited for modeling social networks as they captu...

0 Jialong Zhou, et al. ∙

research

∙ 08/02/2023

Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach

Graph anomaly detection (GAD) has achieved success and has been widely a...

0 Xing Ai, et al. ∙

research

∙ 07/26/2023

Dual-Space Attacks against Random-Walk-based Anomaly Detection

Random Walks-based Anomaly Detection (RWAD) is commonly used to identify...

0 Yuni Lai, et al. ∙

research

∙ 07/24/2023

Homophily-Driven Sanitation View for Robust Graph Contrastive Learning

We investigate adversarial robustness of unsupervised Graph Contrastive ...

0 Yulin Zhu, et al. ∙

research

∙ 02/17/2023

Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks

A physics-informed neural network (PINN) embedded with the susceptible-i...

0 Shuai Han, et al. ∙

research

∙ 02/01/2023

Simple yet Effective Gradient-Free Graph Convolutional Networks

Linearized Graph Neural Networks (GNNs) have attracted great attention i...

0 Yulin Zhu, et al. ∙

research

∙ 11/08/2022

How Fraudster Detection Contributes to Robust Recommendation

The adversarial robustness of recommendation systems under node injectio...

0 Yuni Lai, et al. ∙

research

∙ 10/25/2022

FocusedCleaner: Sanitizing Poisoned Graphs for Robust GNN-based Node Classification

Recently, a lot of research attention has been devoted to exploring Web ...

0 Yulin Zhu, et al. ∙

research

∙ 06/27/2022

Towards Secrecy-Aware Attacks Against Trust Prediction in Signed Graphs

Signed graphs are widely used to model the trust relationships among use...

0 Yulin Zhu, et al. ∙

research

∙ 06/16/2022

Adversarial Robustness of Graph-based Anomaly Detection

Graph-based anomaly detection is becoming prevalent due to the powerful ...

0 Yulin Zhu, et al. ∙

research

∙ 03/01/2022

SMTNet: Hierarchical cavitation intensity recognition based on sub-main transfer network

With the rapid development of smart manufacturing, data-driven machinery...

0 Yu Sha, et al. ∙

research

∙ 03/01/2022

A multi-task learning for cavitation detection and cavitation intensity recognition of valve acoustic signals

With the rapid development of smart manufacturing, data-driven machinery...

0 Yu Sha, et al. ∙

research

∙ 02/26/2022

Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space

Anomalous sound detection (ASD) is one of the most significant tasks of ...

0 Yu Sha, et al. ∙

research

∙ 02/26/2022

An acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering

Valves are widely used in industrial and domestic pipeline systems. Howe...

0 Yu Sha, et al. ∙

research

∙ 12/20/2021

A Multi-user Oriented Live Free-viewpoint Video Streaming System Based On View Interpolation

As an important application form of immersive multimedia services, free-...

7 Jingchuan Hu, et al. ∙

research

∙ 12/12/2021

Automatic differentiation approach for reconstructing spectral functions with neural networks

Reconstructing spectral functions from Euclidean Green's functions is an...

0 Lingxiao Wang, et al. ∙

research

∙ 11/29/2021

Reconstructing spectral functions via automatic differentiation

Reconstructing spectral functions from Euclidean Green's functions is an...

0 Lingxiao Wang, et al. ∙

research

∙ 09/19/2021

Probabilistic Bearing Fault Diagnosis Using Gaussian Process with Tailored Feature Extraction

Rolling bearings are subject to various faults due to its long-time oper...

0 Mingxuan Liang, et al. ∙

research

∙ 07/01/2021

Shared Data and Algorithms for Deep Learning in Fundamental Physics

We introduce a collection of datasets from fundamental physics research ...

0 Lisa Benato, et al. ∙

research

∙ 06/18/2021

BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection

Graph-based Anomaly Detection (GAD) is becoming prevalent due to the pow...

0 Yulin Zhu, et al. ∙

research

∙ 11/30/2020

Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk

As the COVID-19 pandemic continues to ravage the world, it is of critica...

0 Lingxiao Wang, et al. ∙

research

∙ 11/02/2020

Blocking Adversarial Influence in Social Networks

While social networks are widely used as a media for information diffusi...

0 Feiran Jia, et al. ∙

research

∙ 09/29/2020

Enhanced Bayesian Model Updating with Incomplete Modal Information Using Parallel, Interactive and Adaptive Markov Chains

Finite element model updating is challenging because 1) the problem is o...

0 Kai Zhou, et al. ∙

research

∙ 07/26/2020

Robust Collective Classification against Structural Attacks

Collective learning methods exploit relations among data points to enhan...

0 Kai Zhou, et al. ∙

research

∙ 05/07/2020

Efficient Characterization of Dynamic Response Variation Using Multi-Fidelity Data Fusion through Composite Neural Network

Uncertainties in a structure is inevitable, which generally lead to vari...

0 Kai Zhou, et al. ∙

research

∙ 04/16/2020

Structural Model Updating Using Adaptive Multi-Response Gaussian Process Meta-modeling

Finite element model updating utilizing frequency response functions as ...

0 Kai Zhou, et al. ∙

research

∙ 02/12/2020

Uncertainty Quantification of Mode Shape Variation Utilizing Multi-Level Multi-Response Gaussian Process

Mode shape information play the essential role in deciding the spatial p...

0 Kai Zhou, et al. ∙

research

∙ 01/23/2020

Bayesian estimates of transmission line outage rates that consider line dependencies

Transmission line outage rates are fundamental to power system reliabili...

0 Kai Zhou, et al. ∙

research

∙ 11/13/2019

Computing Equilibria in Binary Networked Public Goods Games

Public goods games study the incentives of individuals to contribute to ...

0 Sixie Yu, et al. ∙

research

∙ 09/03/2019

Adversarial Robustness of Similarity-Based Link Prediction

Link prediction is one of the fundamental problems in social network ana...

0 Kai Zhou, et al. ∙

research

∙ 08/09/2019

Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification

Dynamic ensembling of classifiers is an effective approach in processing...

16 Chen Wang, et al. ∙

research

∙ 07/10/2019

Multi-layer Attention Mechanism for Speech Keyword Recognition

As an important part of speech recognition technology, automatic speech ...

2 Ruisen Luo, et al. ∙

research

∙ 09/22/2018

Adversarial Link Prediction in Social Networks

Link prediction is one of the fundamental tools in social network analys...

0 Kai Zhou, et al. ∙

research

∙ 09/12/2018

Security and Privacy Enhancement for Outsourced Biometric Identification

A lot of research has been focused on secure outsourcing of biometric id...

0 Kai Zhou, et al. ∙

research

∙ 09/01/2018

Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network

Link prediction is one of the fundamental research problems in network a...

0 Marcin Waniek, et al. ∙

research

∙ 01/08/2018

P-MOD: Secure Privilege-Based Multilevel Organizational Data-Sharing in Cloud Computing

Cloud computing has changed the way enterprises store, access and share ...

0 Ehab Zaghloul, et al. ∙

research

∙ 11/14/2017

PassBio: Privacy-Preserving User-Centric Biometric Authentication

The proliferation of online biometric authentication has necessitated se...

0 Kai Zhou, et al. ∙

Kai Zhou

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