An AI‐assisted resource scheduling and cooperative learning model in a space–air–ground combined network (SAGIN) to possess ultra‐reliable low‐latency Internet of Medical Things applications and a multi agent—deep deterministic policy gradient (MA‐DDPG) agent that allocates resources in a distributed manner and a hiera...
T. Sardar, Gousia Thahniyath, Ahlam I. Almusharraf et al.· Transactions on Emerging Tel...· 0 citations
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data sources without directly exchanging data. However, FL systems are vulnerable to Byzantine attacks, where malicious participants can inject faulty model updates, compromising model accuracy and potentially causi...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
An experimental deployment of the proposed modular artificial intelligence framework showed improved detection accuracy and faster responsiveness compared to conventional diagnostic methods, highlighting the framework’s potential to improve fault diagnostics.
Faisal Shaikh, Sudipt Panta, R. R. Kumar et al.· Scientific Reports· 0 citations
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data, preserving data privacy. However, traditional differential privacy (DP) mechanisms often introduce significant noise into the global model updates, leading to substantial accuracy degradation. This paper prese...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
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Electroencephalography (EEG)-based Brain-Computer Interface (BCI) systems can support attention monitoring through non-invasive brain signal analysis.This study focuses on passive EEG attention classification for personalized cognitive tracking.A major problem is that EEG signals vary across clients, and non-independen...
Vijayakumar Kempuraj, C. Lakshmi· International Journal of Int...· 0 citations
Reproducibility package for the manuscript "DEx-FCL: Drift- and Explanation-Consistent Federated Continual Learning for Adaptive Edge-IoT Security Management." This release includes the DEx-FCL source code, deterministic federated partitioning utilities, fixed five-seed configurations, CICIoT2023 and Edge-IIoTset bench...
Arul Selvam P· Zenodo (CERN European Organi...· 0 citations
This paper presents a novel approach to decentralized federated learning that leverages the strengths of differential privacy and homomorphic encryption to achieve robust privacy guarantees. The core idea is to encrypt each participant's local data using homomorphic encryption, allowing a central server to perform comp...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper explores the application of federated learning (FL) as a novel approach to privacy-preserving data analysis. Traditional data analysis methods often require centralized data collection, raising significant privacy concerns. Federated learning offers a compelling alternative by enabling collaborative model tr...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Reproducibility package for the manuscript "DEx-FCL: Drift- and Explanation-Consistent Federated Continual Learning for Adaptive Edge-IoT Security Management." This release includes the DEx-FCL source code, deterministic federated partitioning utilities, fixed five-seed configurations, CICIoT2023 and Edge-IIoTset bench...
Arul Selvam P· Zenodo (CERN European Organi...· 0 citations
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data, preserving data privacy. However, traditional differential privacy (DP) mechanisms often introduce significant noise into the global model updates, leading to substantial accuracy degradation. This paper prese...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper presents a novel approach to generative modeling by integrating Generative Adversarial Networks (GANs) with Federated Learning (FL). Traditional GAN training suffers from centralized data requirements and privacy concerns. This research addresses these limitations through a distributed GAN architecture speci...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Credit card transaction fraud has resulted in a massive loss to both consumers and banks in recent years.As a result, this research proposes an optimized framework for fraud detection.This framework will allow banks to construct fraud detection models using training data stored in their internal database.With this appr...
Mustafa Abdul Salam, Doaa Elbably· International journal of int...· 0 citations
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
