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Showing 1 to 7 of 7 for “"Model Generalizability"”.

  1. Achieving More with Less: Learning Generalizable Neural Networks With Less Labeled Data and Computational Overheads

    … datasets and using highly compute-intensive models. Many applications cannot afford these costs needed to ensure generalizability of deep learning models. For instance, obtaining labeled data can be costly in scientific applications, and using large models may not be feasible in …

    vt Repository record for Achieving More with Less: Learning Generalizable Neural Networks With Less Labeled Data and Computational Overheads (opens in a new tab)

  2. Detecting Bots using Stream-based System with Data Synthesis

    … bot detection. However, many machine learning models are difficult to deploy since model training requires the continuous supply of representative labeled data, which are expensive and time-consuming to obtain in practice. In this thesis, we build a bot detection system with a data synthesis …

    vt Repository record for Detecting Bots using Stream-based System with Data Synthesis (opens in a new tab)

  3. Weisfeiler-Leman graph kernels for the out-of-distribution characterization of graph structured data

    … Neural Networks (GNNs) without introducing a new model architecture. Within existing GNN research, strong claims of out-of-distribution (OOD) generalizability are frequently made, but these claims fail when exposed to real-world data. We propose existing standards of identifying OOD data are …

    umkc Repository record for Weisfeiler-Leman graph kernels for the out-of-distribution characterization of graph structured data (opens in a new tab)

  4. Image-Based Spatial Change Detection Using Deep Learning

    … detail of the predicted outputs, and the notable model performance degradation when the target data have different characteristics from the training data. This research contributes to the development and evaluation of novel DL methods and algorithms for automated image-based spatial change …

    york Repository record for Image-Based Spatial Change Detection Using Deep Learning (opens in a new tab)

  5. A Patient Risk Minimization Model for Post-Disaster Medical Delivery Using Unmanned Aircraft Systems

    … of this research was to develop a novel routing model for delivery of medical supplies using unmanned aircraft systems, improving existing vehicle routing models by using patient risk as the primary minimization variable.</p> <p>The vehicle routing problem is a subset of operational research that …

    embry-riddle Repository record for A Patient Risk Minimization Model for Post-Disaster Medical Delivery Using Unmanned Aircraft Systems (opens in a new tab)

  6. Online Joint Identification of Structural Dynamic Response Anomalies and Structural Damage Using Limited Data

    … degrade data reliability; the lack of adaptive model updates restricts performance under changing environmental and operational conditions; and accurate damage diagnosis is often impeded by the scarcity of labeled damage data, which limits model generalizability and diagnostic accuracy. To …

    poli-torino Repository record for Online Joint Identification of Structural Dynamic Response Anomalies and Structural Damage Using Limited Data (opens in a new tab)

  7. Advancing Cross-Domain Fake News Detection: Enhanced Models to Improve Generalization and Tackle the Class Imbalance Problem

    … concerns, and adversarial exploitation of these models. Several challenges hinder the effectiveness of current FND models. Among these, cross-domain generalization and class imbalance are two critical problems that considerably impact the performance of detection systems. Although there are …

    ottawa-retro Repository record for Advancing Cross-Domain Fake News Detection: Enhanced Models to Improve Generalization and Tackle the Class Imbalance Problem (opens in a new tab)