Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...

This note examines the utility of pseudorandom variables (prv) in Global Search and Optimization (GSO) using Central Force Optimization (CFO) as an example. Most GSO metaheuristics are stochastic in ...

Abstract: The random Kaczmarz (RK) algorithm is an iterative method to solve overdetermined linear systems and serves as a representative example of row action methods. In this paper, we propose a ...

Currently, the demo/ directory has limited examples demonstrating the use of the algorithms. Adding more Python examples will help new users understand how to work with the different algorithms ...

Researchers have successfully used a quantum algorithm to solve a complex century-old mathematical problem long considered impossible for even the most powerful conventional supercomputers. The ...

Abstract: A probabilistic approach is considered for robust optimization, where a convex objective function is minimized subject to a parameter dependent convex constraint. A novel sequential ...

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I (94) esp_image: segment 0: paddr=00010020 vaddr=3f400020 size=1e314h (123668) map I (133) esp_image: segment 1: paddr=0002e33c vaddr=3ff80000 size=0001ch ( 28) load I (133) esp_image: segment 2: ...

One July afternoon in 2024, Ryan Williams set out to prove himself wrong. Two months had passed since he’d hit upon a startling discovery about the relationship between time and memory in computing.

High-quality random number generators are required for various applications such as cryptography, secure communications, Monte Carlo simulations, and randomized algorithms. Existing pseudorandom ...