Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Even the most modern random number generators do not produce perfectly random numbers, which can be a problem for cryptographic applications. ETH Zurich researchers use entangled superconducting ...

Researchers have developed a chip-based quantum random number generator that provides high-speed, high-quality operation on a miniaturized platform. This advance could help move quantum random number ...

Linear, an enterprise software maker that competes with many of Atlassian’s products, on Tuesday announced that it raised $82 million in a Series C funding round led by Accel. The round, which also ...

Abstract: With its inherent causal reasoning and superior capacity for handling uncertainty, the belief rule base (BRB) has been widely applied in complex systems modeling. As a generalization of ...

Random number generation is an essential feature in Excel, allowing users to perform tasks such as simulations, creating test datasets, or experimenting with spreadsheet models. Excel provides three ...

We present a machine learning method based on random projections with Johnson-Lindenstrauss (JL) and/or Rahimi and Recht (2007) Random Fourier Features (RFFN) for efficiently learning linear and ...

When you have a density function, but you would like to create a set of sample points from that density function, you can use linear interpolate sampling. Using the evaluation of the density at the ...

ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...

Motivation: Family-based study design is one of the popular designs used in genetic research, and the whole-genome sequencing data obtained from family-based studies offer many unique features for ...