Results 171 to 180 of about 7,049,980 (289)

Methods for Uncertainty Quantification in Dictionary Matching to Advance Reliability of Quantitative MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Aims Purpose: Dictionary matching is a standard tool in quantitative MRI (qMRI), but typically lacks uncertainty quantification (UQ). This is critical when advanced reconstructions (e.g., compressed sensing, deep learning) introduce complex‐valued, spatially varying, and temporally correlated noise that violates standard assumptions of ...
Brian Toner, Ute Goerke, Eze Ahanonu, Kevin Johnson, Vibhas Deshpande, Holden H. Wu, Maria I. Altbach, Ali Bilgin   +7 more
wiley   +1 more source

Privacy-preserving federated learning with optimized ensemble weighting and knowledge distillation for COVID-19 detection from non-IID medical imaging data. [PDF]

Sci Rep
Annan R, Qin H, Newman R, Siddula M, Qingge L.   +4 more
europepmc   +1 more source

Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance

Naval Research Logistics (NRL), EarlyView.
ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley   +1 more source

Federated Learning for Human Pose Estimation on Non-IID Data via Gradient Coordination. [PDF]

Sensors (Basel)
Ni P, Xiang D, Jiang D, Sun J, Cui J.
europepmc   +1 more source

Chromatic PAC-Bayes Bounds for Non-IID Data.

, 2009
Pac-Bayes bounds are among the most accurate generalization bounds for classifiers learned with \iid data, and it is particularly so for margin classifiers. However, there are many practical cases where the training data show some dependencies and where the traditional \iid assumption does not apply.
Ralaivola, Liva, Szafranski, Marie, Stempfel, Guillaume   +2 more
openaire   +2 more sources

Reconsidering Volume‐Based Drug Procurement Policy: The Consequences of Manufacturers' Optimal Production Planning and Breach Strategies

Naval Research Logistics (NRL), EarlyView.
ABSTRACT This paper examines the impacts of Volume‐Based Procurement (VBP) policies on pharmaceutical supply chains, with a focus on the strategic behaviors of manufacturers. VBP aims to reduce costs and stabilize supplies by centralizing procurement through competition based on volumes and prices.
Nani Zhou, Tong Wang, Guohua Wan
wiley   +1 more source

FD-IDS: Federated Learning with Knowledge Distillation for Intrusion Detection in Non-IID IoT Environments. [PDF]

Sensors (Basel)
Peng H, Wu C, Xiao Y.
europepmc   +1 more source

The Weak Core, Partition‐Based Universal Stability, and Their Risk Associations Through A Partial Order

Naval Research Logistics (NRL), EarlyView.
ABSTRACT We are concerned with the stability of a transferable‐utility cooperative (TU) game. First, the concept of core can be weakened so that the blocking of changes is limited to only those with multilateral backings. This principle of consensual blocking, as well as the traditional core‐defining one of unilateral blocking and one straddling in ...
Jian Yang
wiley   +1 more source

Information Design for Early‐Stage Dose‐Finding Trials

Naval Research Logistics (NRL), EarlyView.
ABSTRACT To enhance enrollment rates in early‐stage dose‐finding clinical trials, we propose an information design approach, where the clinical investigator (CI) commits to an information releasing mechanism (IRM) based on the treatment's uncertain efficacy and toxicity to encourage patients to participate in the trial.
Amin Khademi, Ningyuan Chen
wiley   +1 more source

Federated Learning Framework for Brain Tumor Detection Using MRI Images in Non-IID Data Distributions. [PDF]

J Imaging Inform Med
Muntaqim MDZ, Smrity TA.
europepmc   +1 more source