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 pavpanchekha.com
Floating Point Error in Polynomials
| | marc-b-reynolds.github.io
A fast path floating point underflow test elision from absorption
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| | A sketch of a fast path filter to avoid explicit underflow checking following an addition or subtraction.
| | www.jeremykun.com
Polynomial Multiplication Using the FFT || Math ? Programming
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| | Problem: Compute the product of two polynomials efficiently. Solution: import numpy from numpy.fft import fft, ifft def poly_mul(p1, p2): """Multiply two polynomials. p1 and p2 are arrays of coefficients in degree-increasing order. """ deg1 = p1.shape[0] - 1 deg2 = p1.shape[0] - 1 # Would be 2*(deg1 + deg2) + 1, but the next-power-of-2 handles the +1 total_num_pts = 2 * (deg1 + deg2) next_power_of_2 = 1 << (total_num_pts - 1).
| | orlp.net
Ordering Numbers, How Hard Can It Be? | orlp.net
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| | [AI summary] A deep dive into the complexities and pitfalls of comparing different numeric types (integers and floating-point) across various programming languages and the CPU architecture
| | golb.hplar.ch
Building a simple neural network with Java and JavaScript
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| [AI summary] The blog post details the author's experience implementing a feedforward neural network for digit recognition using Java and JavaScript, explaining the underlying algorithms, shared external libraries, and architectural decisions while reviewing an introductory book on the topic.