Results 31 to 40 of about 12,931,660 (289)
Regularizing Label-Augmented Generative Adversarial Networks Under Limited Data
IEEE Access, 2023 Training generative adversarial networks (GANs) using limited training data is challenging since the original discriminator is prone to overfitting. The recently proposed label augmentation technique complements categorical data augmentation approaches ...
Liang Hou
doaj +1 more source
Feature Reconstruction from Incomplete Tomographic Data without Detour
Mathematics, 2022 In this paper, we consider the problem of feature reconstruction from incomplete X-ray CT data. Such incomplete data problems occur when the number of measured X-rays is restricted either due to limit radiation exposure or due to practical constraints ...
Simon Göppel +2 more
doaj +1 more source
A Few-Shot Learning Based Fault Diagnosis Model Using Sensors Data from Industrial Machineries
Vibration, 2023 Efficient maintenance in the face of complex and interconnected industrial equipment is crucial for corporate competitiveness. Traditional reactive approaches often prove inadequate, necessitating a shift towards proactive strategies.
Farhan Md. Siraj +2 more
doaj +1 more source
BMJ OpenObjectives To quantify and describe the use of real-world data (RWD) in National Institute for Health and Care Excellence (NICE) oncology technology appraisal (TA) final appraisal determination documents.Design A systematic literature review was ...
Lewis Carpenter +3 more
doaj +1 more source
Estimating coherence measures from limited experimental data available
, 2018 Quantifying coherence has received increasing attention, and considerable work has been directed towards finding coherence measures. While various coherence measures have been proposed in theory, an important issue following is how to estimate these ...
Liu, C. L. +3 more
core +1 more source
Anonymizing Trajectory Data: Limitations and Opportunities
, 2022 A variety of conditions and limiting properties complicate the anonymization of trajectory data, since they are sequential, high-dimensional, bound to geophysical restrictions and easily mapped to semantic points of interest and regions with known properties like suburban neighborhoods, industrial areas or city-centers.
Guerra Balboa, Patricia +4 more
openaire +4 more sources
Limits with modeling data and modeling data with limits
Data Science Journal, 2002 Modeling of the solubility of amino acids and purine and pyrimidine bases with a set of sixteen molecular descriptors has been thoroughly analyzed to detect and understand the reasons for anomalies in the description of this property for these two classes of compounds.
openaire +4 more sources
Stochastic Optimization from Distributed, Streaming Data in Rate-limited Networks
, 2018 Motivated by machine learning applications in networks of sensors, internet-of-things (IoT) devices, and autonomous agents, we propose techniques for distributed stochastic convex learning from high-rate data streams.
Bajwa, Waheed U., Nokleby, Matthew
core +1 more source
Journal of Business Economics and Management, 2017 Multiple uncertainties complicate socio-economic forecasting problems, especially when relying on ill-conditioned limited data. Such problems are best addressed by grey prediction models such as Grey Verhulst Model (GVM).
Mohammad Hashem-Nazari +2 more
doaj +1 more source
Identifying Finite-Time Coherent Sets from Limited Quantities of Lagrangian Data
, 2015 A data-driven procedure for identifying the dominant transport barriers in a time-varying flow from limited quantities of Lagrangian data is presented. Our approach partitions state space into pairs of coherent sets, which are sets of initial conditions ...
Rowley, Clarence W. +2 more
core +1 more source