Experiments conducted in a controlled simulation environment show that BFGRL can effectively improve security, trust management, scalability, and operational efficienssssscy in blockchain-assisted smart EV networks.
K. Ambika, R. Gopi, S. S et al.· Scientific Reports· 0 citations
FedRAT is proposed, a privacy-preserving federated framework that couples paired paraphrase consistency, generator-family auxiliary supervision, differentially private client updates, and loss-dependent aggregation within a unified detection setting.
Zi-Hao Zhang· International journal of pat...· 0 citations
This deposit provides the software and reproducibility evidence for Precision and Coverage in Robust Federated Learning. It includes compressed client-update codecs, robust aggregation, seven development candidates and a complete five-seed comparison of three methods. Archived checkpoints, predictions, confusion matric...
This code-only package accompanies the manuscript “Federated Edge Learning over Optical-UAV Access Links With Deterministic-Payload Compression and Packetized Scheduling.”The software implements static mixed-resolution compression with error feedback (SMR-EF) and PacketFair scheduling for simulated federated learning o...
The increasing penetration of renewable energy sources introduces significant variability and uncertainty into grid-connected microgrids (MGs), affecting voltage stability, frequency regulation, power quality, fault ride-through capability, and operational resilience at the Point of Common Coupling (PCC). These challen...
Nicholas Nyaika, Cosmas Mwikirize, Andrew Katumba· Zenodo (CERN European Organi...· 0 citations
"AV-Stack-Eval is a reproducible research dataset for comparing classical and AI-based methods across the autonomous vehicle (AV) software stack. It packages the inputs, source code, per-replicate results, summary statistics, tables and figures of twelve controlled experiments (E1\u2013E12). The experiments cover perce...
Code accompanying "FedREST-HIDS: Split-Federated Intrusion Detection for Resource-Heterogeneous Industrial IoT" (Vyas, Hwang & Lin), submitted to Computer Communications. FedREST-HIDS partitions intrusion detection across three tiers. Resource-rich devices train complete local models and take part in federated learning...
Code accompanying "FedREST-HIDS: Split-Federated Intrusion Detection for Resource-Heterogeneous Industrial IoT" (Vyas, Hwang & Lin), submitted to Computer Communications. FedREST-HIDS partitions intrusion detection across three tiers. Resource-rich devices train complete local models and take part in federated learning...
A Federated Temporal-Aware Lightweight IDS (FTL-IDS) that co-designs multi-domain CAN feature extraction, an LSTM–Transformer temporal encoder, 8-bit quantization-aware training (QAT), and federated learning (FL).
Hamed Alqahtani, Gulshan Kumar· Multimedia tools and applica...· 0 citations
The increasing penetration of renewable energy sources introduces significant variability and uncertainty into grid-connected microgrids (MGs), affecting voltage stability, frequency regulation, power quality, fault ride-through capability, and operational resilience at the Point of Common Coupling (PCC). These challen...
Nicholas Nyaika, Cosmas Mwikirize, Andrew Katumba· Zenodo (CERN European Organi...· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026