Deep Learning (DL) techniques are widely deployed in critical applications such as autonomous driving, healthcare, and intelligent infrastructure. Core paradigms—Deep Neural Networks (DNNs), Deep Reinforcement Learning (DRL), Federated Learning (FL), and Transfer Learning (TL)—remain vulnerable to adversarial attacks t...
Mamoon Ahmed Yahay Al Khadher· Iconic Research and Engineer...· 0 citations
FedLucra, a modular loss‐aware aggregation framework that jointly uses client validation loss and local data volume to determine aggregation weights, is proposed and the proposed loss‐aware privacy mechanisms can improve model utility relative to uniform‐budget differential privacy in several evaluated settings.
Emin Akpinar, M. Taşkıran, Bulent Bolat· Expert systems· 0 citations
A critical translational synthesis of oncology databases and computational resources used to predict tumor radiosensitivity and chemosensitivity and shows homologous recombination deficiency in the context of DNA-damaging therapy and genomic-adjusted radiation dose as a research predictor of radiotherapy benefit is dem...
I. A. Solovev, D. Golubev· Real-World Data & Eviden...· 0 citations
Federated learning (FL) has emerged as a transformative framework in artificial intelligence, addressing escalating concerns around data privacy, security, and distributed computation. Unlike conventional centralized learning systems that require data aggregation, FL enables collaborative model training across multiple...
Sonam Gupta, Pradeep Gupta· 0 citations
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Abstract What happens when algebra usurps political power? Studies in digital mobility predominantly focus on utilitarian geometric route optimization. However, this paradigm overlooks the fact that navigation algorithms operate as concealed normative actors, thereby distributing the right to the city. Drawing upon a s...
Oleksandr Hlushenko· Zenodo (CERN European Organi...· 0 citations
A novel Federated Anomaly Detection for Heterogeneous Smart Home Environment-based Zero-Trust Micro-Segmentation (CloudShield-IoT) framework is introduced, demonstrating strong resilience against Byzantine adversarial attacks.
Cross-border healthcare data sharing is critical to advance precision treatment, rare illness research, and global public health surveillance. However, legislative limits, privacy concerns, and institutional mistrust severely impede centralized data pooling across nations. Federated learning (FL) has emerged as a poten...
Reference implementation of SWIFT, a wait-free decentralized federated learning algorithm in which clients never block on one another: each broadcasts its model to its neighbours and averages in whatever has arrived. SWIFT is the first asynchronous decentralized federated learning algorithm to obtain the optimal O(1/sq...
Marco Bornstein, Tahseen Rabbani, Evan Wang et al.· Zenodo (CERN European Organi...· 0 citations
Healthcare information technology (IT) infrastructure has grown substantially in complexity alongside the accelerating adoption of electronic health records, clinical decision support systems, telehealth platforms, and patient-facing digital services. Managing this infrastructure reliably under high availability expect...
Nayan Kumar Sureshbhai Patel· Journal of Information Syste...· 0 citations
The majority of the work now in publication discusses safeguard healthcare data however, the data modality—text, photos, audio, and sound—was not particularly addressed. Additionally, it was unclear how to safeguard while taking into account the differences in feature extraction depending on the input modalities. To de...
ReSIDS / ereno-Adaptativo is an intrusion-detection pipeline that unifies centralized, federated and gossip learning in a single run with round-by-round mode switching, built on Flower, scikit-learn and XGBoost. Version 2 adds: a distributed, automatic FL↔GL switch driven by decentralized failure detection (fail-fast F...
CassioBatista, Paulo Coelho, Silvio E. Quincozes et al.· Zenodo (CERN European Organi...· 0 citations
Abstract What happens when algebra usurps political power? Studies in digital mobility predominantly focus on utilitarian geometric route optimization. However, this paradigm overlooks the fact that navigation algorithms operate as concealed normative actors, thereby distributing the right to the city. Drawing upon a s...
Oleksandr Hlushenko· Zenodo (CERN European Organi...· 0 citations
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.
