AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,057 papers
Research code and frozen reproducibility artifacts for decision identifiability in one-shot federated learning.
ource code accompanying the TrustFed-RL manuscript on multi-signal behavioural trust, trust-weighted federated learning, RL-based cyber response, and runtime governance for IoMT intrusion detection. This release includes: Core modules (src/): FL client/server, trust, governance, RL, adversary Locked experiment configs...
Software archive accompanying the paper "Who Benefits from Federation? Heterogeneous Gains in Cross-Operator Network Traffic Representation Learning" by Mohammad Arafath Uddin Shariff and Byrav Ramamurthy (School of Computing, University of Nebraska-Lincoln), presented at the 13th International Workshop on Innovating t...
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The rapid expansion of the Internet of Things (IoT) introduces complex, multi-layered security challenges that centralized security models and conventional intrusion detection systems struggle to address. This paper presents a multi-layer security framework that integrates Blockchain for decentralized trust management,...
As system decentralization heterogeneous resource constraints and the uncertain threat against quantum computing are introduced by rapid growth of edge-cloud computing infrastructures, this develop also raises new security challenges.Traditional security architectures depend on stationary cryptographic deployments and...
HRA-TS provides an effective and practical solution for personalized career recommendation in dynamic and privacy-sensitive environments and employs a hybrid long short-term memory–graph attention network encoder to jointly capture users’ evolving behavioral evolution and stable personal attributes.
Artificial intelligence (AI) and Machine learning (ML) are transforming the pharmaceutical lifecycle—from target identification and lead optimization to clinical development, manufacturing, supply chain orchestration, and real-world pharmacovigilance. This review synthesizes recent advances (2018–2025) across core meth...
Artificial intelligence (AI) is altering plant biotechnology by solving significant problems in tissue culture and bioreactor systems, including variability, man-power intensity, and poor reproducibility. Machine learning (ML) algorithms and artificial neural networks (ANNs) have opened the capability of simulating com...
In this paper, three operations on Gibbs probability measures are studied. The first operation, often referred to as renormalization, takes one Gibbs probability measure and generates a new Gibbs measure by normalizing a power of its density. This normalization has a twofold effect: it changes the regularization factor...
Federated Learning (FL) enables privacy-preserving distributed machine learning by keeping raw data local. However, conventional Artificial Neural Networks (ANNs) impose high computational and energy costs. Spiking Neural Networks (SNNs), inspired by biological neurons, provide energy-efficient computation via sparse s...
CardioHealth-FL: Synthetic Cardiovascular Healthcare Dataset CardioHealth-FL is a rule-based synthetic healthcare dataset developed for cardiovascular risk and federated learning research. It contains 40,000 records, 16 features, and a target variable, Cardiovascular_Risk. The records were generated using predefined pr...
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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