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louisabraham.github.io | ||
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aneesh.mataroa.blog
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bayesianneuron.com
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| | | | | [AI summary] The user has shared a detailed exploration of optimizing the 0/1 Knapsack problem using dynamic programming with Python and NumPy. They discuss various optimization techniques, including reducing memory usage with a 2-row approach, vectorization using NumPy's `np.where` for faster computation, and the performance improvements achieved. The final implementation shows significant speedups, especially for large-scale problems, and the user highlights the importance of vectorization and efficient memory management in computational tasks. | |
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kevinkle.in
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| | | | | I modeled solving a Sudoku board as a constraint optimization problem. | |
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www.jeremykun.com
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| | | So far in this series we've seen elliptic curves from many perspectives, including the elementary, algebraic, and programmatic ones. We implemented finite field arithmetic and connected it to our elliptic curve code. So we're in a perfect position to feast on the main course: how do we use elliptic curves to actually do cryptography? History As the reader has heard countless times in this series, an elliptic curve is a geometric object whose points have a surprising and well-defined notion of addition. | ||
