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Showing 1 to 3 of 3 for “"Coordinate-search"”.

  1. Proposing effective coordinate search methods for solving large-scale expensive black-box optimization problems

    … several novel optimization algorithms based on Coordinate Search (CS) algorithm are proposed. CS is a gradient-free technique and we have enhanced them for solving Black-box, non-convex, and expensive large-scale problems. These CS-based algorithms can handle mixed-type variables. When an …

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  2. Novel optimizers for multi-objective deep learning

    … the Adam optimizer operates without independent searching agents. Therefore, the global search is not permissible as multiple agents do not communicate with one another. In this thesis, we introduced a population-based Adam optimizer and incorporated it into the framework of multi-objective …

    uoit Repository record for Novel optimizers for multi-objective deep learning (opens in a new tab)

  3. New frontiers in population-based multi-objective feature selection

    … general, is a NP-hard problem since the size of search space increases exponentially by the increase of the number of features, so especially in high-dimensional spaces, it can be very challenging. We propose three innovative approaches to tackle large-scale multi-objective feature selection. The …

    uoit Repository record for New frontiers in population-based multi-objective feature selection (opens in a new tab)