Nonconvex optimization issues are prevalent in machine learning and data science. While gradient-based optimization algorithms can rapidly converge and are dimension-independent, they may, ...

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Permanent magnet arc motor (PMAM) is widely used in some scanning systems, such as the astronomical telescopes and large antennas. In order to address the optimization design of the PMAM, a new ...

Subsequently, a distributed primal–dual hybrid gradient algorithm (dPDHG) for quantile regression is proposed, and its convergence is analyzed. 3.1 Diffusion-based distributed estimation framework ...

This is an unofficial PyTorch implementation of End-to-end Driving via Conditional Imitation Learning. All credit to the original researchers. The dataset can be downloaded here. It is 24GB of HDF5 ...

Conclusion The t-SNE algorithm provides an effective method to visualize a complex dataset. It successfully uncovers hidden structures in the data, exposing natural clusters and smooth nonlinear ...