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2,057 papers
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...
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...
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...
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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...
Conventional intrusion detection systems (IDSs) are not suitable for large-scale, heterogeneous, and privacy-sensitive cloud environments, owing to the rapid adoption of cloud computing and Internet of Things (IoT) technologies, which have resulted in an increasing scale and complexity of cyberattacks. Current machine...
Advanced drug delivery systems (DDS) — including polymeric and lipid nanoparticles, lipid nanoparticles (LNPs) for nucleic acid therapeutics, solid oral dosage forms, and three-dimensional (3D)-printed and stimuli-responsive platforms — require the simultaneous optimization of dozens of interacting formulation and proc...
Advanced drug delivery systems (DDS) — including polymeric and lipid nanoparticles, lipid nanoparticles (LNPs) for nucleic acid therapeutics, solid oral dosage forms, and three-dimensional (3D)-printed and stimuli-responsive platforms — require the simultaneous optimization of dozens of interacting formulation and proc...
Edge computing has gained significant traction in recent years, promising enhanced efficiency by integrating artificial intelligence capabilities at the edge. While the focus has primarily been on the deployment and inference of Machine Learning (ML) models at the edge, the training aspect remains less explored. This s...
Privacy remains a significant barrier to unlocking the full potential of AI in sensitive domains such as healthcare. In this chapter, we survey methods for preserving privacy while enabling useful data analysis. We review anonymization approaches, including k-anonymity, differential privacy, and federated learning, and...
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.
Education Innovation
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
A Blog post by NVIDIA on Hugging Face
A Blog post by IBM Research on Hugging Face
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
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