Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

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 ...

Here's the corrected and polished version: Implementation of randomized greedy algorithms for solving the Knapsack Problem and Traveling Salesman Problem in C++. Educational project demonstrating ...

Jake Peterson is Lifehacker’s Tech Editor, and has been covering tech news and how-tos for nearly a decade. His team covers all things technology, including AI, smartphones, computers, game consoles, ...

Abstract: In undirected graphs with real non-negative weights, we give a new randomized algorithm for the single-source shortest path (SSSP) problem with running time ...

Abstract: Distributed detection over decentralized baseband architectures has emerged as an important problem in the uplink massive MIMO systems. In this paper, the classic Kaczmarz method is fully ...

The second you start watching a video on YouTube, the site begins building an algorithm of your likes. While the goal of that is to show you content you want to see, it means you'll miss out on so ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

The proposal suggests implementing a shared random algorithm to eliminate Maximal Extractable Value (MEV) at the block level and distribute block construction more equitably across the network. An ...