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Showing 1 to 5 of 5 for “"Singular value thresholding"”.

  1. Robust synthetic control

    … is that of de-noising the data matrix via singular value thresholding, which renders our approach robust in multiple facets: it automatically identifies a good subset of donors, functions without extraneous covariates (vital to existing methods), and overcomes missing data (never been …

    mit Repository record for Robust synthetic control (opens in a new tab)

  2. Gain Conditioning for Linear Model Predictive Control

    … methods based on relative gain arrays and singular-value thresholding to condition their gain matrices to prevent degraded controller performance. These techniques tend to require many iterations to successfully condition a large gain matrix. In the proposed approach I extend an …

    queens Repository record for Gain Conditioning for Linear Model Predictive Control (opens in a new tab)

  3. A Novel Image Retrieval Strategy Based on VPD and Depth with Pre-Processing

    … It is an extension of the traditional singular value thresholding (SVT) algorithm, addressing the issue that SVT cannot recover a matrix with missing rows or columns. Proposed is a way to fill such rows and columns, and then apply SVT to restore the damaged image. The pre-filled entries …

    siu-theses Repository record for A Novel Image Retrieval Strategy Based on VPD and Depth with Pre-Processing (opens in a new tab)

  4. Addressing Missing Data and Scalable Optimization for Data-driven Decision Making

    … can be contaminated by noise, or even by missing values. Second, building a model from data usually involves solving an optimization problem, which may require prohibitively large computational resources. In this thesis, we explore two research directions, motivated by these two challenges. In the …

    mit Repository record for Addressing Missing Data and Scalable Optimization for Data-driven Decision Making (opens in a new tab)