b'Qiang Yang'

research

∙ 05/24/2023

Theoretically Principled Federated Learning for Balancing Privacy and Utility

We propose a general learning framework for the protection mechanisms th...

0 Xiaojin Zhang, et al. ∙

research

∙ 05/19/2023

A Topic-aware Summarization Framework with Different Modal Side Information

Automatic summarization plays an important role in the exponential docum...

0 Xiuying Chen, et al. ∙

research

∙ 05/10/2023

FedSOV: Federated Model Secure Ownership Verification with Unforgeable Signature

Federated learning allows multiple parties to collaborate in learning a ...

0 Wenyuan Yang, et al. ∙

research

∙ 05/08/2023

FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof

Federated learning (FL) allows multiple parties to cooperatively learn a...

0 Wenyuan Yang, et al. ∙

research

∙ 05/07/2023

Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion

Federated learning (FL) enables participating parties to collaboratively...

0 Xiaojin Zhang, et al. ∙

research

∙ 04/21/2023

Learn to Cluster Faces with Better Subgraphs

Face clustering can provide pseudo-labels to the massive unlabeled face ...

0 Yuan Cao, et al. ∙

research

∙ 04/11/2023

A Game-theoretic Framework for Federated Learning

In federated learning, benign participants aim to optimize a global mode...

0 Xiaojin Zhang, et al. ∙

research

∙ 04/10/2023

Probably Approximately Correct Federated Learning

Federated learning (FL) is a new distributed learning paradigm, with pri...

0 Xiaojin Zhang, et al. ∙

research

∙ 11/24/2022

FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders

This paper proposes a general spectral analysis framework that thwarts a...

0 Hanlin Gu, et al. ∙

research

∙ 11/14/2022

FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model

Copyright protection of the Federated Learning (FL) model has become a m...

0 Shuo Shao, et al. ∙

research

∙ 10/10/2022

A Survey on Heterogeneous Federated Learning

Federated learning (FL) has been proposed to protect data privacy and vi...

0 Dashan Gao, et al. ∙

research

∙ 08/28/2022

Cross-domain Cross-architecture Black-box Attacks on Fine-tuned Models with Transferred Evolutionary Strategies

Fine-tuning can be vulnerable to adversarial attacks. Existing works abo...

0 Yinghua Zhang, et al. ∙

research

∙ 07/09/2022

Federated Learning with Quantum Secure Aggregation

This article illustrates a novel Quantum Secure Aggregation (QSA) scheme...

0 Yichi Zhang, et al. ∙

research

∙ 06/21/2022

An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Application

Recently, the artificial intelligence of things (AIoT) has been gaining ...

0 Youlong Ding, et al. ∙

research

∙ 06/21/2022

WrapperFL: A Model Agnostic Plug-in for Industrial Federated Learning

Federated learning, as a privacy-preserving collaborative machine learni...

0 Xueyang Wu, et al. ∙

research

∙ 05/27/2022

FadMan: Federated Anomaly Detection across Multiple Attributed Networks

Anomaly subgraph detection has been widely used in various applications,...

0 Nannan Wu, et al. ∙

research

∙ 04/21/2022

Hybrid Cloud-Edge Collaborative Data Anomaly Detection in Industrial Sensor Networks

Industrial control systems (ICSs) are facing increasing cyber-physical a...

2 Tao Yang, et al. ∙

research

∙ 03/11/2022

No free lunch theorem for security and utility in federated learning

In a federated learning scenario where multiple parties jointly learn a ...

0 Xiaojin Zhang, et al. ∙

research

∙ 03/10/2022

A Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling Technologies,and Challenges

Dubbed "the successor to the mobile Internet", the concept of the Metave...

0 Minrui Xu, et al. ∙

research

∙ 01/05/2022

Realizing the Metaverse with Edge Intelligence: A Match Made in Heaven

Dubbed "the successor to the mobile Internet", the concept of the Metave...

0 Wei Yang Bryan Lim, et al. ∙

research

∙ 12/15/2021

LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization

Federated optimization (FedOpt), which targets at collaboratively traini...

0 Huiming Chen, et al. ∙

research

∙ 10/12/2021

SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary

Sports game summarization aims to generate news articles from live text ...

0 Jiaan Wang, et al. ∙

research

∙ 09/27/2021

FedIPR: Ownership Verification for Federated Deep Neural Network Models

Federated learning models must be protected against plagiarism since the...

6 Lixin Fan, et al. ∙

research

∙ 09/19/2021

Multi-Task Learning in Natural Language Processing: An Overview

Deep learning approaches have achieved great success in the field of Nat...

0 Shijie Chen, et al. ∙

research

∙ 08/19/2021

QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction

We study the problem of query attribute value extraction, which aims to ...

11 Danqing Zhang, et al. ∙

research

∙ 08/18/2021

Practical and Secure Federated Recommendation with Personalized Masks

Federated recommendation is a new notion of private distributed recommen...

0 Liu Yang, et al. ∙

research

∙ 08/06/2021

Transferring Knowledge Distillation for Multilingual Social Event Detection

Recently published graph neural networks (GNNs) show promising performan...

8 Jiaqian Ren, et al. ∙

research

∙ 06/30/2021

CityNet: A Multi-city Multi-modal Dataset for Smart City Applications

Data-driven approaches have been applied to many problems in urban compu...

0 Xu Geng, et al. ∙

research

∙ 06/17/2021

Frustratingly Easy Transferability Estimation

Transferability estimation has been an essential tool in selecting a pre...

3 Long-Kai Huang, et al. ∙

research

∙ 05/19/2021

Federated Singular Vector Decomposition

With the promulgation of data protection laws (e.g., GDPR in 2018), priv...

0 Di Chai, et al. ∙

research

∙ 03/16/2021

Ternary Hashing

This paper proposes a novel ternary hash encoding for learning to hash m...

0 Chang Liu, et al. ∙

research

∙ 03/01/2021

Towards Personalized Federated Learning

As artificial intelligence (AI)-empowered applications become widespread...

0 Alysa Ziying Tan, et al. ∙

research

∙ 02/17/2021

A Game-theoretic Approach Towards Collaborative Coded Computation Offloading

Coded distributed computing (CDC) has emerged as a promising approach be...

0 Jer Shyuan Ng, et al. ∙

research

∙ 02/08/2021

Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack

Ever since Machine Learning as a Service (MLaaS) emerges as a viable bus...

15 Ding Sheng Ong, et al. ∙

research

∙ 01/12/2021

TrNews: Heterogeneous User-Interest Transfer Learning for News Recommendation

We investigate how to solve the cross-corpus news recommendation for uns...

0 Guangneng Hu, et al. ∙

research

∙ 12/07/2020

Privacy and Robustness in Federated Learning: Attacks and Defenses

As data are increasingly being stored in different silos and societies b...

0 Lingjuan Lyu, et al. ∙

research

∙ 11/27/2020

Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness

Deep neural networks (DNNs) are known to be prone to adversarial attacks...

0 Yilun Jin, et al. ∙

research

∙ 11/19/2020

FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning

As an innovative solution for privacy-preserving machine learning (ML), ...

0 Di Chai, et al. ∙

research

∙ 10/16/2020

PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation

Transfer learning is an effective technique to improve a target recommen...

0 Guangneng Hu, et al. ∙

research

∙ 08/25/2020

Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning

Transfer learning has become a common practice for training deep learnin...

21 Yinghua Zhang, et al. ∙

research

∙ 08/25/2020

Protect, Show, Attend and Tell: Image Captioning Model with Ownership Protection

By and large, existing Intellectual Property Right (IPR) protection on d...

2 Jian Han Lim, et al. ∙

research

∙ 07/03/2020

Privacy Threats Against Federated Matrix Factorization

Matrix Factorization has been very successful in practical recommendatio...

7 Dashan Gao, et al. ∙

research

∙ 06/20/2020

Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

This paper investigates capabilities of Privacy-Preserving Deep Learning...

19 Lixin Fan, et al. ∙

research

∙ 06/18/2020

SenWave: Monitoring the Global Sentiments under the COVID-19 Pandemic

Since the first alert launched by the World Health Organization (5 Janua...

1 Qiang Yang, et al. ∙

research

∙ 05/31/2020

Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning

In 5G and Beyond networks, Artificial Intelligence applications are expe...

0 Wei Yang Bryan Lim, et al. ∙

research

∙ 05/22/2020

Graph Random Neural Network

Graph neural networks (GNNs) have generalized deep learning methods into...

57 Wenzheng Feng, et al. ∙

research

∙ 05/20/2020

Network On Network for Tabular Data Classification in Real-world Applications

Tabular data is the most common data format adopted by our customers ran...

2 Yuanfei Luo, et al. ∙

research

∙ 03/12/2020

Fisher Deep Domain Adaptation

Deep domain adaptation models learn a neural network in an unlabeled tar...

10 Yinghua Zhang, et al. ∙

research

∙ 03/04/2020

Threats to Federated Learning: A Survey

With the emergence of data silos and popular privacy awareness, the trad...

25 Lingjuan Lyu, et al. ∙

research

∙ 02/26/2020

A Survey towards Federated Semi-supervised Learning

The success of Artificial Intelligence (AI) should be largely attributed...

23 Yilun Jin, et al. ∙

Qiang Yang

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