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2,117 papers
The complexity of emerging cyber threats renders the need for intelligent, adaptive and real-time responses essential. In this paper, an explainable deep learning assisted federated learning and adversarial robustness-based AI-enabled threat detection scheme for cybersecurity is introduced. The framework also breaks th...
The CUST-Iris dataset was collected at Capital University of Science and Technology (CUST), Islamabad, Pakistan, for biometric iris recognition research. The dataset contains 2,880 iris images acquired from 720 unique irises (L+R) using the Crossmatch I-Scan 2 iris scanner. Images were captured in the near-infrared (NI...
This paper studies federated learning for nonparametric regression in the context of distributed samples across different servers, each adhering to distinct differential privacy constraints. The setting we consider is heterogeneous, encompassing both varying sample sizes and differential privacy constraints across serv...
The global imperative to decarbonise road transport has required the automotive and energy sectors to reconceptualise vehicular powertrain engineering across all scales, from atomic-level electrochemistry to fleet-level grid interaction. This PRISMA-compliant systematic review synthesises 120 peer-reviewed publications...
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The results show that colluding semi-honest nodes can recover the original local updates of honest nodes, enabling downstream reconstruction of private training data, and demonstrate that SA alone does not guarantee privacy in DFL when local aggregation induces asymmetric observations.
To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) exploits waveform superposition over multiple-access channels (MACs) for analog model aggregation. However, coherent AirFL typically relies on stringent PHY-layer condition...
This work proposes geographically regularized AUC-maximizing personalized federated learning (GrAUC-PFL), which directly optimizes a smooth pairwise AUC surrogate to learn personalized models while keeping patient-level data local and accounting for institutional heterogeneity.
This paper shows that the proposed method ensures a bounded Byzantine influence on both distillation gradients and individual client private gradients after cross-modality fusion, thereby enabling stable local optimization for honest clients under Byzantine distillation.
A fine-grained distributed backdoor attack framework that uses dynamic trigger generation and embedding vector optimization to perform attacks with fewer poisoned samples and introduces an embedding vector contrastive learning strategy that forces poisoned samples to approach the target class center in the feature spac...
A constrained Bayesian Optimization framework for the efficient configuration of HFL deployments that captures user-defined trade-offs among energy consumption, execution time, and predictive performance, while explicit constraints ensure compliance with deployment-specific resource and accuracy requirements.
One-shot federated graph learning generally aims to train Graph Neural Networks (GNNs) across clients with disconnected subgraphs in a single communication round. Existing methods predominantly design advanced optimization strategies under the premise that local GNN training is indispensable. However, empirical observa...
CALM is proposed, which replaces every hard decision with a smooth trust gate at three levels: per class, teachers are weighted by agreement with the peer consensus; per sample, distillation is scaled by the teachers'divergence from that target; and a label gate scales it by how strongly the target supports the sample'...
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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