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08/23/2023
A Survey for Federated Learning Evaluations: Goals and Measures
Evaluation is a systematic approach to assessing how well a system achie...
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08/04/2023
DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization
Time series remains one of the most challenging modalities in machine le...
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07/06/2023
A Survey on Evaluation of Large Language Models
Large language models (LLMs) are gaining increasing popularity in both a...
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05/24/2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility
We propose a general learning framework for the protection mechanisms th...
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05/19/2023
A Topic-aware Summarization Framework with Different Modal Side Information
Automatic summarization plays an important role in the exponential docum...
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05/10/2023
FedSOV: Federated Model Secure Ownership Verification with Unforgeable Signature
Federated learning allows multiple parties to collaborate in learning a ...
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05/08/2023
FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Federated learning (FL) allows multiple parties to cooperatively learn a...
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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...
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04/21/2023
Learn to Cluster Faces with Better Subgraphs
Face clustering can provide pseudo-labels to the massive unlabeled face ...
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04/11/2023
A Game-theoretic Framework for Federated Learning
In federated learning, benign participants aim to optimize a global mode...
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04/10/2023
Probably Approximately Correct Federated Learning
Federated learning (FL) is a new distributed learning paradigm, with pri...
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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...
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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...
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10/10/2022
A Survey on Heterogeneous Federated Learning
Federated learning (FL) has been proposed to protect data privacy and vi...
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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...
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07/09/2022
Federated Learning with Quantum Secure Aggregation
This article illustrates a novel Quantum Secure Aggregation (QSA) scheme...
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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 ...
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06/21/2022
WrapperFL: A Model Agnostic Plug-in for Industrial Federated Learning
Federated learning, as a privacy-preserving collaborative machine learni...
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05/27/2022
FadMan: Federated Anomaly Detection across Multiple Attributed Networks
Anomaly subgraph detection has been widely used in various applications,...
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04/21/2022
Hybrid Cloud-Edge Collaborative Data Anomaly Detection in Industrial Sensor Networks
Industrial control systems (ICSs) are facing increasing cyber-physical a...
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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 ...
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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...
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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...
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12/15/2021
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization
Federated optimization (FedOpt), which targets at collaboratively traini...
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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 ...
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09/27/2021
FedIPR: Ownership Verification for Federated Deep Neural Network Models
Federated learning models must be protected against plagiarism since the...
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09/19/2021
Multi-Task Learning in Natural Language Processing: An Overview
Deep learning approaches have achieved great success in the field of Nat...
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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 ...
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08/18/2021
Practical and Secure Federated Recommendation with Personalized Masks
Federated recommendation is a new notion of private distributed recommen...
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08/06/2021
Transferring Knowledge Distillation for Multilingual Social Event Detection
Recently published graph neural networks (GNNs) show promising performan...
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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...
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06/17/2021
Frustratingly Easy Transferability Estimation
Transferability estimation has been an essential tool in selecting a pre...
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05/19/2021
Federated Singular Vector Decomposition
With the promulgation of data protection laws (e.g., GDPR in 2018), priv...
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03/16/2021
Ternary Hashing
This paper proposes a novel ternary hash encoding for learning to hash m...
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03/01/2021
Towards Personalized Federated Learning
As artificial intelligence (AI)-empowered applications become widespread...
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02/17/2021
A Game-theoretic Approach Towards Collaborative Coded Computation Offloading
Coded distributed computing (CDC) has emerged as a promising approach be...
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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...
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01/12/2021
TrNews: Heterogeneous User-Interest Transfer Learning for News Recommendation
We investigate how to solve the cross-corpus news recommendation for uns...
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12/07/2020
Privacy and Robustness in Federated Learning: Attacks and Defenses
As data are increasingly being stored in different silos and societies b...
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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...
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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), ...
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10/16/2020
PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation
Transfer learning is an effective technique to improve a target recommen...
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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...
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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...
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07/03/2020
Privacy Threats Against Federated Matrix Factorization
Matrix Factorization has been very successful in practical recommendatio...
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06/20/2020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
This paper investigates capabilities of Privacy-Preserving Deep Learning...
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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...
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05/31/2020
Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning
In 5G and Beyond networks, Artificial Intelligence applications are expe...
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05/22/2020
Graph Random Neural Network
Graph neural networks (GNNs) have generalized deep learning methods into...
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05/20/2020
