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ENTITY Learning using privileged information: SVM+ and weighted SVM.

Learning using privileged information: SVM+ and weighted SVM.

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  1. TOOL · CL_252101 ·

    New PAC-Bayesian Framework Quantifies Value of Privileged Information in ML

    Researchers have developed a new PAC-Bayesian framework to quantify the value of privileged information (PI) in machine learning. This approach offers an algorithm-agnostic method to estimate the potential knowledge tra…

  2. TOOL · CL_204320 ·

    TRACE-GS framework enhances 3D Gaussian Splatting restoration with privileged geometry

    Researchers have introduced TRACE-GS, a novel framework for improving 3D Gaussian Splatting (3DGS) restoration, particularly in sparse-view scenarios. This method employs on-policy trajectory distillation, using privile…

  3. TOOL · CL_104665 ·

    New SMO Algorithm Enhances One-Class SVM Training with Privileged Information

    Researchers have developed a new Sequential Minimal Optimization (SMO) algorithm specifically for One-Class Support Vector Machines with Privileged Information (OC-SVM+). This novel approach aims to address a gap in exi…