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convex-optimisation · GitHub Topics · GitHub

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convex-optimisation

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Collected study materials in Numerical Optimization ANU@MATH3514(HPC)

  • Updated May 6, 2019

Stochastic Gradient Descent (SGD) is an optimization algorithm that updates model parameters iteratively using small, random subsets (batches) of data, rather than the entire dataset. It significantly speeds up training for large datasets, though it introduces noise that causes, in some cases, heavy fluctuations.deep learning/neural networks.solver

  • Updated Mar 17, 2026
  • Jupyter Notebook

MSc Thesis at Indra on real-time onboard successive convexification (SCvx) with quadratic programming (QP) for powered landing guidance of reusable space launchers

  • Updated Mar 24, 2026

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