federated learning

AMAF-FCL: Adaptive Multi-Factor Accurate Forgetting for Heterogeneous Federated Continual Learning

Results indicate that multi-factor reliability assessment and heterogeneity-aware adaptive forgetting improve the balance between useful knowledge retention and harmful-knowledge suppression in heterogeneous FCL.

Navigating committor landscape of biomolecules with a general pairwise interaction model

A novel committor learning framework grounded in the AlphaFold 3 paradigm is proposed that elucidates how ligand substituents regulate the ratio between distinct binding pathways, offering new perspectives for structure-based drug design.

Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.

The Comprehensive VS Platform with AI Engine (CVSP-AIE) for drug discovery from compound libraries integrates three AI models: KarmaDock, a fast docking model that directly updates atomic coordinates; CarsiDock, an accurate docking model that predicts protein-ligand distances and reconstructs binding poses; and RTMScor...

An Explicit Interaction-Prompted Diffusion Framework for High-Fidelity 3D Molecular Generation.

Current structure-based drug design generative models often struggle to faithfully recapitulate genuine ligand-protein binding interactions. Instead, under the coupling of implicit learning architectures and biased training data, they tend to learn spurious statistical correlations. To address this, we propose EIP-Diff...

FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning

Two distinct effects are reported: paired-example FedAvg partially recovers the missing-ECG gap, while validation-selected completion is a task-specific classifier-logit correction rather than literal ECG recovery.

AoI Minimization in Heterogeneous MEC Networks: A Federated Learning-Assisted Hybrid DRL and Convex Approach

This paper investigates a dynamic heterogeneous mobile edge computing network (HMECN), where mobile devices (MDs) could offload their full tasks to a small base station (SBS) directly or the macro base station (MBS) in direct or relay mode. As age of information (AoI) is a comprehensive and accurate metric to capture t...

A Decentralized Learning Architecture for Medical Prescription Anomaly Detection via Hybrid Federated-Swarm Learning

The increasing use of electronic medical records (EMRs) has improved efficiency, accuracy, and accessibility of patient data. However, conventional centralized architectures suffer from single points of failure and data privacy issues. To address these challenges, this study proposes a decentralized machine learning ar...

PA-FedVL: A privacy-enhanced federated virtual learning framework based on label differential privacy distillation

Boosting Gradient-Based Training Diagnosis for Efficient and Accurate Federated Learning

Federated Learning (FL) allows edge clients to collaborate in model training with data privacy preserved, yet it is known to suffer low training efficiency and model accuracy. Given that efficiency and accuracy are usually conflicting objectives, existing practices increasingly employ an adaptive scheme that changes th...

STDFL: A Spatio-Temporal-Aware Dynamic Federated Learning Framework for Spatial Crowdsourcing

Spatial Mobile Crowdsourcing (SMC) faces the dual challenge of ensuring privacy while managing dynamic, Non-IID spatio-temporal data. While Federated Learning (FL) offers a privacy-preserving solution, traditional aggregation suffers from severe model drift due to evolving spatio-temporal contexts. Furthermore, existin...

Battery-Aware Dynamic Adaptive Low-Power Device Selection for IoT-Enabled FL Networks

The integration of Internet of Things (IoT) and Federated Learning (FL) marks a significant step towards pervasiveness, supported by distributed computational resources and enhanced by 5G advancements. However, the efficient and sustainable operation of IoT-enabled FL systems faces critical challenges, particularly in...

DPFL-GM: A dynamic privacy federated learning framework with gradual maturity mechanism