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Implementations of gradKCCA
Black-Box optimization of a rotor's shape using Projected Gradient Descent
Non-negative Matrix Factorization based on cuda, with sparse matrix as input.
CUDA Non-negative Matrix Factorization (NMF) based on cuMF
All sorts of data science & computer science programs for future reference
SVM algorithms implementation from scratch for AI539 class project
This project was carried out as the final assignment for the Mathematical Optimization for Data Science course. The goal of the analysis was to compare two variants of the Frank-Wolfe Method with the Projected Gradient Method on the Markowitz portfolio optimization problem.
Non-linear topology identification using Deep Learning. Sparsity (lasso) is enforced in the sensor connections. The non-convex and non-differentiable function is solved using sub-gradient descent algorithm.