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Found 3 papers, 1 papers with code
A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions
Upon this transformation, we propose a distributed methodology based on the cognitive-based adaptive optimization (CAO) algorithm, that is able to approximate the evolution of each robot's cost function and to adequately optimize its decision variables (robot actions).
Investigating the Vision Transformer Model for Image Retrieval Tasks
This paper introduces a plug-and-play descriptor that can be effectively adopted for image retrieval tasks without prior initialization or preparation.
A Gradient Free Neural Network Framework Based on Universal Approximation Theorem
The proposed algorithm adheres to the underlying theory, is highly fast, and results in remarkably low errors when applied for regression and classification of complex data-sets, such as the Griewank function of multiple variables $\mathbf{x} \in \mathbb{R}^{100}$ with random noise addition, and MNIST database for handwritten digits recognition, with $7\times10^4$ images.
