7 papers
Conformal Fusion Under Missing Modalities
Alireza Moayedikia
Multimodal fusion architectures typically assume all modalities are available at inference, yet sensor failures, acquisition variability, and cost constraints routinely produce inc…
Capacity Confounds and Coverage Guarantees in Adaptive Sub-model Federated Learning
Alireza Moayedikia, Alicia Troncoso Lora
Sub-model federated learning lets resource-constrained clients train width-reduced versions of a global model, but existing methods allocate capacity by device resources alone. A n…
Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction
Alireza Moayedikia, Sara Fin, Alicia Troncoso Lora +1
Predicting conversion from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) is critical for early intervention. Current deep learning paradigms predominantly rely on cro…
Alzheimer's Disease Brain Network Mining
Alireza Moayedikia, Sara Fin
Machine learning approaches for Alzheimer's disease (AD) diagnosis face a fundamental challenges. Clinical assessments are expensive and invasive, leaving ground truth labels avail…
Bridging Training and Merging Through Momentum-Aware Optimization
Alireza Moayedikia, Alicia Troncoso
Training large neural networks and merging task-specific models both exploit low-rank structure and require parameter importance estimation, yet these challenges have been pursued…
Attention Fusion for Bridge Deck Delamination Detection
Alireza Moayedikia, Amirhossein Moayedikia
Subsurface delaminations in reinforced concrete bridge decks escape conventional visual inspection, and the two principal sensing techniques used to find them are individually inco…